CN105453128A - Portable computing device and analyses of personal data captured therefrom - Google Patents

Portable computing device and analyses of personal data captured therefrom Download PDF

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Publication number
CN105453128A
CN105453128A CN201480042461.3A CN201480042461A CN105453128A CN 105453128 A CN105453128 A CN 105453128A CN 201480042461 A CN201480042461 A CN 201480042461A CN 105453128 A CN105453128 A CN 105453128A
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China
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described
exercise
user
comprises
embodiments
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CN201480042461.3A
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Chinese (zh)
Inventor
托马斯·李·莱克二世
迈克尔·卡斯帕里安
彼得·李
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阿特拉斯维拉伯斯公司
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Application filed by 阿特拉斯维拉伯斯公司 filed Critical 阿特拉斯维拉伯斯公司
Priority to PCT/US2014/048972 priority patent/WO2014194337A1/en
Publication of CN105453128A publication Critical patent/CN105453128A/en

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Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00335Recognising movements or behaviour, e.g. recognition of gestures, dynamic facial expressions; Lip-reading
    • G06K9/00342Recognition of whole body movements, e.g. for sport training
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B21/00Exercising apparatus for developing or strengthening the muscles or joints of the body by working against a counterforce, with or without measuring devices
    • A63B21/06User-manipulated weights
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B71/00Games or sports accessories not covered in groups A63B1/00 - A63B69/00
    • A63B71/06Indicating or scoring devices for games or players, or for other sports activities
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G06F19/3481Computer-assisted prescription or delivery of treatment by physical action, e.g. surgery or physical exercise
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10Services
    • G06Q50/22Social work
    • GPHYSICS
    • G09EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09BEDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B19/00Teaching not covered by other main groups of this subclass
    • G09B19/003Repetitive work cycles; Sequence of movements
    • G09B19/0038Sports
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/30ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2220/00Measuring of physical parameters relating to sporting activity
    • A63B2220/17Counting, e.g. counting periodical movements, revolutions or cycles, or including further data processing to determine distances or speed
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2220/00Measuring of physical parameters relating to sporting activity
    • A63B2220/30Speed
    • A63B2220/34Angular speed
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2220/00Measuring of physical parameters relating to sporting activity
    • A63B2220/40Acceleration
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2230/00Measuring physiological parameters of the user
    • A63B2230/04Measuring physiological parameters of the user heartbeat characteristics, e.g. E.G.C., blood pressure modulations
    • A63B2230/06Measuring physiological parameters of the user heartbeat characteristics, e.g. E.G.C., blood pressure modulations heartbeat rate only
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2230/00Measuring physiological parameters of the user
    • A63B2230/40Measuring physiological parameters of the user respiratory characteristics
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2230/00Measuring physiological parameters of the user
    • A63B2230/50Measuring physiological parameters of the user temperature
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2230/00Measuring physiological parameters of the user
    • A63B2230/65Measuring physiological parameters of the user skin conductivity
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/20Analysis of motion
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/63ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders

Abstract

A personal computing device comprising: a processor, an onboard memory, an accelerometer, a gyroscope, and a display; a computer program to create an exercise analysis application comprising: a software module configured to receive data from the accelerometer and the gyroscope that are associated with the bodily motion of a user in three dimensions; a software module configured to place the device in a learning mode, the learning mode comprising recording the data of the user performing a defined exercise to generate a statistical model for the exercise; a software module configured to place the device in a normal mode, the normal mode comprising applying a probabilistic analysis to the bodily motion data to identify an exercise event, classify the exercise by comparison to a recorded model; and a software module configured to apply an analysis to the bodily motion data to score the user's exercise form.

Description

Portable computing device and the analysis to the personal data caught from it

the cross reference of related application

The application is the non-provisional application of the U.S. Provisional Application numbers 61/828,680 submitted on May 30th, 2013 and requires its rights and interests, and the full content of this provisional application is incorporated into this by reference.

Background technology

Physical fitness is all useful to individual in every respect.For example, physical fitness reduce disease risk, help avoid injured and quality of making the life better.Health pliability, muscle strength, basal metabolic rate, cardiovascular endurance and body fat rate are the exemplary indicator of physical fitness.Physical training maintain and improve individual healthy in play key player.Physical training is also worked in alleviation work or relevant pressure of living.For example, weight training specifically provides many functional benefits; It strengthens muscle power to improve bearing and to provide better support for joint.In addition, weight training increases muscle quality, this then cause the rising of basic metabolism; Higher speed promotes long-term fat reducing and reduces the risk of chronic fatty relevant disease.

Summary of the invention

Physical training is of value to the healthy of individual as everyone knows.But if do not carried out with suitable intensity, amount and duration, then physical training may be unfavorable to the health of individual.In addition, if physical training is not correctly carried out, then unnecessary damage may be there is.Traditional sports equipment can provide some information relevant with the intensity of activity, amount and duration, but this type of information is limited to minority activity.The exercise that private religion is some provides feedback and training; But, for routine work feedback and training may be not too afford and inconvenience.

An advantage of equipment described herein, platform and medium is, they provides for convenient to identify, monitor and record the means of various sports.Utilize its learning ability, add easily and store the type of new sports, for exercise in the future and study.Thus user can select from sports that are far-ranging, that will monitor and follow the tracks of.Further, the physiological parameter of monitor user ' while of when taking exercise, to carry out physical training with the intensity of the best, amount and duration for individual consumer.Another important advantage is, quantitative comparison is carried out in the performance of user and expert, and provides feedback to promote the raising of effectively study and performance.Generally speaking, equipment described herein, platform and medium can utilize feedback to realize study efficiently, can realize sensitivity monitoring, the storage to physical training and identify easily.

In an aspect, this document describes personal computing devices, described personal computing devices comprises: processor, plate carry storer, accelerometer, gyroscope and display; Comprise the computer program that can be performed to create by digital processing device the instruction that exercise analysis is applied, the application of described exercise analysis comprises: be arranged to and receive acceleration information and from the software module of described gyroscope acceptance angle speed data, described acceleration information and described angular velocity data are associated with the body kinematics of user under three dimensions from described accelerometer; Be arranged to the software module described equipment being placed in mode of learning, described mode of learning comprises acceleration information and the angular velocity data that record carries out the described user of the exercise defined, to generate the statistics exercise model for described exercise; Be arranged to the software module described equipment being placed in normal mode, described normal mode comprises described acceleration information and the analysis of described angular velocity data applied probability to identify exercise event, classified by the comparing of exercise model with record and identified the multiplicity of described exercise described exercise; And be arranged to described acceleration information and the analysis of described angular velocity data applied statistics with the software module of marking to the exercise posture of described user.In some embodiments, to be suitable for user wearable for described equipment.In further embodiment, described equipment is suitable for can be worn by described user's wrist.In further embodiment, described equipment comprises wearable adapter, and described wearable adapter reversibly can connect from described equipment, to form modular design.In some embodiments, the processor being arranged to exercise analysis application also comprises software module, and described software module is used for comprising biology sensor further, to measure the physiological parameter of described user.In further embodiment, described biology sensor is selected from and comprises every group below: heart rate monitor, thermometer, respirometer, glucose monitoring devices, electrolyte sensor and diagometer.In further embodiment, described biology sensor is optical biosensor.In further embodiment, described physiological parameter is selected from and comprises following group: heart rate, skin temperature, respiratory rate, electrodermal response and aquation.In further embodiment, described application also comprises the software module being arranged to and presenting graphic user interface, and described graphic user interface comprises the rest timer based on heart rate.In some embodiments, described personal computing devices also comprises Geographical Location element.In some embodiments, described equipment also comprises wireless communication unit.In further embodiment, described wireless communication unit is bluetooth module or ANT+ module.In some embodiments, be used for comprising the probability analysis that described exercise is classified utilizing neural network, context tree weighting, hidden Markov model or its combination.In some embodiments, scoring comes from the body steadiness of described user, the sports coordination of described user or its combination at least in part.In some embodiments, described scoring comes from comparing of the exercise model of described acceleration information and described angular velocity data and the data genaration by other users at least in part.In some embodiments, described scoring comes from comparing of described acceleration information and described angular velocity data and the exercise model generated by one or more suitable lattice body-building professional person at least in part.In some embodiments, described exercise is one-sided weight training or bilateral weight training.In some embodiments, described application also comprises the software module being arranged to and presenting user interface over the display, and described user interface comprises described scoring, described exercise, described multiplicity, combines specific to the message of taking exercise or its.In further embodiment, described exercise is weight training, and the described message specific to taking exercise be selected from comprise below suggestion in every group: weight is too heavy, weight is too light, weight change excessive, motion is too fast, health too not steadily, fault, posture be too inharmonious and about the rectification opinion of posture.

In another aspect, this document describes exercise analysis platform, described exercise analysis platform comprises: personal computing devices, it comprises processor, plate carries storer, accelerometer, gyroscope, display and communication device, described equipment is arranged to provides individual exercise analysis to apply, described individual exercise analysis application comprises: be arranged to and receive acceleration information and from the software module of described gyroscope acceptance angle speed data from described accelerometer, described acceleration information and described angular velocity data are associated with the body kinematics of user under three dimensions, be arranged to the software module to acceleration information described in exercise analysis server application transport and angular velocity data, described exercise analysis platform comprises processor-server, described processor-server is arranged to provides exercise analysis server to apply, the application of this exercise analysis server comprises: the database of statistics exercise model, and described exercise model is generated by the acceleration information of user and angular velocity data carrying out the exercise defined, be arranged to the software module receiving acceleration information and angular velocity data from described personal computing devices, be arranged to described acceleration information and the analysis of described angular velocity data applied probability with identify exercise event, by with one or more the comparing and described exercise classified and identifies the software module of the multiplicity of described exercise in described statistics exercise model, be arranged to described acceleration information and the analysis of described angular velocity data applied statistics with the software module of marking to the exercise posture of described user.In some embodiments, described platform comprises at least 100, at least 1000 or at least 10,000 personal computing devices.In some embodiments, described individual exercise analysis application also comprises the software module being arranged to and described personal computing devices being placed in mode of learning, described mode of learning comprises acceleration information and the angular velocity data that record carries out the described user of the exercise defined, to generate the statistics exercise model for described exercise.In some embodiments, the database of described statistics exercise model comprises at least 10, at least 50, at least 100 or at least 500 exercise model, and each exercise model is associated with specific exercise.In some embodiments, each exercise model is generated by the average data of the multiple users from the exercise carrying out defining.In further embodiment, it is on average the weighted mean of the professional skill level based on each user.In some embodiments, one or more exercise model is by the data genaration of the one or more suitable lattice body-building professional person from the exercise carrying out defining.In further embodiment, one or more exercise model is by from correctly not carrying out defined exercise to simulate the data genaration of the suitable lattice body-building professional of common exercise posture problem.In further embodiment, one or more exercise model is by the data genaration of suitable lattice body-building professional of tempering posture from the exercise correctly carrying out defining with illustrated example.In some embodiments, to be suitable for user wearable for described personal computing devices.In some embodiments, described personal computing devices is suitable for and can be worn by described user's wrist.In further embodiment, described personal computing devices comprises wearable adapter, and described wearable adapter reversibly can connect from described personal computing devices, to form modular design.In some embodiments, described personal computing devices also comprises biology sensor, is used for measuring the physiological parameter of described user.In further embodiment, described biology sensor is selected from and comprises every group below: heart rate monitor, thermometer, respirometer, glucose monitoring devices, electrolyte sensor and diagometer.In further embodiment, described biology sensor is optical biosensor.In further embodiment, physiological parameter is selected from and comprises every group below: heart rate, skin temperature, respiratory rate, electrodermal response and aquation.In further embodiment, described individual exercise analysis application or the application of described server also comprise the software module being arranged to and presenting graphic user interface, and described graphical user interface comprises the rest timer based on heart rate.In some embodiments, described personal computing devices also comprises Geographical Location element.In some embodiments, described communication device is wireless communication unit.In further embodiment, described wireless communication unit is bluetooth module or ANT+ module.In some embodiments, be used for comprising the probability analysis that described exercise is classified utilizing neural network, context tree weighting, hidden Markov model or its combination.In some embodiments, described scoring comes from the body steadiness of described user, the sports coordination of described user or its combination at least in part.In some embodiments, described scoring comes from comparing of described acceleration information and described angular velocity data and the exercise model generated by suitable lattice body-building professional person at least in part.In some embodiments, described exercise is one-sided weight training or bilateral weight training.In some embodiments, described individual exercise analysis application or the application of described server also comprise the software module being arranged to and presenting user interface on the display of described personal computing devices, and described user interface comprises described scoring, described exercise, described multiplicity, combines specific to the message of taking exercise or its.In further embodiment, described exercise is weight training, and the described message specific to taking exercise be selected from comprise below suggestion in every group: weight is too heavy, weight is too light, weight change too many, motion is too fast, health too not steadily, fault, posture be too inharmonious and about the rectification opinion of posture.In some embodiments, the transmission that described acceleration information and angular velocity data are applied to exercise analysis server is direct.In some embodiments, the transmission that described acceleration information and angular velocity data are applied to exercise analysis server is indirectly, and first described data are transferred to local device.In some embodiments, described individual exercise analysis application or the application of described server also comprise the software module being arranged to and presenting and allow described user to create the interface of personal profiles, and described profile comprises body weight, height, sex, arm exhibition and body-building professional skill.

In in other, the non-transient computer-readable recording medium being encoded with and can being performed the instruction carrying out individual exercise analysis by processor is disclosed herein, described instruction comprises: be arranged to the software module from comprising accelerometer and gyrostatic personal computing devices reception data, described data comprise from the acceleration information of described accelerometer with from described gyrostatic angular velocity data, and described acceleration information and described angular velocity data are associated with the body kinematics of user under three dimensions; Be arranged to the software module described equipment being placed in mode of learning, described mode of learning comprises acceleration information and the angular velocity data that record carries out the described user of the exercise defined, to generate the statistics exercise model for described exercise; Be arranged to the software module described equipment being placed in normal mode, described normal mode comprises described acceleration information and the analysis of described angular velocity data applied probability to identify exercise event, classified by the comparing of exercise model with record and identified the multiplicity of described exercise described exercise; And be arranged to described acceleration information and the analysis of described angular velocity data applied statistics with the software module of marking to the exercise posture of described user.In some embodiments, to be suitable for user wearable for described personal computing devices.In some embodiments, described personal computing devices is suitable for and can be worn by described user's wrist.In further embodiment, described personal computing devices comprises wearable adapter, and described wearable adapter reversibly can connect from described personal computing devices, to form modular design.In some embodiments, described personal computing devices also comprises biology sensor, is used for measuring the physiological parameter of described user.In further embodiment, described biology sensor is selected from and comprises every group below: heart rate monitor, thermometer, respirometer, glucose monitoring devices, electrolyte sensor and diagometer.In further embodiment, described biology sensor is optical biosensor.In further embodiment, described physiological parameter is selected from and comprises every group below: heart rate, skin temperature, respiratory rate, electrodermal response and aquation.In further embodiment, be arranged to the processor carrying out individual exercise analysis and also comprise the software module being arranged to and presenting graphic user interface, described graphic user interface comprises the rest timer based on heart rate.In some embodiments, described personal computing devices also comprises Geographical Location element.In some embodiments, described personal computing devices also comprises wireless communication unit.In further embodiment, described wireless communication unit is bluetooth module or ANT+ module.In some embodiments, be used for comprising the probability analysis that described exercise is classified utilizing neural network, context tree weighting, hidden Markov model or its combination.In some embodiments, described scoring comes from the body steadiness of described user, the sports coordination of described user or its combination at least in part.In some embodiments, described scoring comes from comparing of the exercise model of described acceleration information and described angular velocity data and the data genaration by other users at least in part.In some embodiments, described scoring comes from comparing of described acceleration information and described angular velocity data and the exercise model generated by one or more suitable lattice body-building professional person at least in part.In some embodiments, described exercise is one-sided weight training or bilateral weight training.In some embodiments, described medium also comprises the software module being arranged to and presenting user interface on the display, and described user interface comprises described scoring, described exercise, described multiplicity, combines specific to the message of taking exercise or its.In further embodiment, described exercise is weight training, and the described message specific to taking exercise be selected from comprise below suggestion in every group: weight is too heavy, weight is too light, weight change too many, motion is too fast, health too not steadily, fault, posture be too inharmonious and about the rectification opinion of posture.

In in other, this document describes the non-transient computer-readable recording medium being encoded with computer program, described computer program comprises the instruction that can be performed to create by processor the application of exercise analysis server, described exercise analysis server application comprises: the database of statistics exercise model, the acceleration information that described exercise model is transmitted by the personal computing devices be associated with the user carrying out the exercise defined and angular velocity data generate, described acceleration information and described angular velocity data comprise X-axis separately, the data of Y-axis and Z axis, described equipment is in mode of learning, be arranged to the software module receiving acceleration information and the angular velocity data transmitted by the personal computing devices be associated with the user carrying out the exercise defined, described equipment is in normal mode, be arranged to and received acceleration information and angular velocity data applied probability analyzed to identify exercise event, by with one or more comparison in described statistics exercise model and described exercise is classified and identifies the software module of the multiplicity of described exercise, be arranged to received acceleration information and the analysis of angular velocity data applied statistics with the software module of marking to the exercise posture of described user.In some embodiments, the data being transferred to described database can wear equipment from least 100, at least 1000 or at least 10000.In some embodiments, the database of statistics exercise model comprises at least 10, at least 50, at least 100 or at least 500 exercise model, and each exercise model is associated with specific exercise.In some embodiments, described personal computing devices comprises processor, plate carries storer, accelerometer and display.Described personal computing devices also comprises gyroscope, magnetometer or altitude gauge.In some embodiments, described activity analysis server application also comprises the software module for receiving data from personal computing devices, and wherein said data transfer to described personal computing devices from accelerometer, gyroscope, magnetometer or altitude gauge.In some embodiments, described individual activity server application is from least 100, at least 1000 or at least 10, and 000 personal computing devices receives data.In some embodiments, described individual activity analytical applications also comprises the software module being arranged to and described personal computing devices being placed in mode of learning, and described mode of learning comprises record and carries out the acceleration information of the described user of the activity defined to generate the statistical activity model for described activity.In some embodiments, each exercise model is generated by the average data of the multiple users from the exercise carrying out defining.In some embodiments, be on average the weighted mean of professional skill level based on each user.In some embodiments, one or more exercise model is by the data genaration of the one or more suitable lattice body-building professional person from the exercise carrying out defining.In further embodiment, one or more exercise model by from the exercise correctly not carrying out defining to simulate the data genaration of the suitable lattice body-building professional of common exercise posture problem.In further embodiment, one or more exercise model is by the data genaration of suitable lattice body-building professional of tempering posture from the exercise correctly carrying out defining with illustrated example.In some embodiments, to be suitable for user wearable for described personal computing devices.In some embodiments, described personal computing devices is suitable for and can be worn by described user's wrist.In further embodiment, described personal computing devices comprises wearable adapter, and described wearable adapter reversibly can connect from described personal computing devices, to form modular design.In some embodiments, described personal computing devices also comprises biology sensor, is used for measuring the physiological parameter of described user.In further embodiment, described biology sensor is selected from and comprises every group below: heart rate monitor, thermometer, respirometer, glucose monitoring devices, electrolyte sensor and diagometer.In further embodiment, described biology sensor is optical biosensor.In further embodiment, described physiological parameter is selected from and comprises every group below: heart rate, skin temperature, respiratory rate, electrodermal response and aquation.In further embodiment, described exercise analysis server application also comprises the software module being arranged to and presenting graphic user interface, and described graphic user interface comprises the rest timer based on heart rate.In some embodiments, described personal computing devices also comprises Geographical Location element.In some embodiments, be used for comprising the probability analysis that described exercise is classified utilizing neural network, context tree weighting, hidden Markov model or its combination.In some embodiments, scoring comes from the body steadiness of described user, the sports coordination of described user or its combination at least in part.In some embodiments, described must scoring comes from comparing of described acceleration information and described angular velocity data and the exercise model generated by suitable lattice body-building professional person at least in part.In some embodiments, described exercise is one-sided weight training or bilateral weight training.In some embodiments, described exercise analysis server application also comprises the software module being arranged to and presenting user interface on the display of described personal computing devices, and described user interface comprises described scoring, described exercise, described multiplicity, combines specific to the message of taking exercise or its.In further embodiment, described exercise is weight training, and the described message specific to taking exercise be selected from comprise below suggestion in every group: weight is too heavy, weight is too light, weight change too many, motion is too fast, health too not steadily, fault, posture be too inharmonious and about the rectification opinion of posture.In some embodiments, the transmission that described acceleration information and angular velocity data are applied to described exercise analysis server is direct.In some embodiments, the transmission that described acceleration information and angular velocity data are applied to described exercise server is indirectly, and first described data are transferred to local device.In some embodiments, described exercise analysis server application also comprises the software module being arranged to and presenting and allow described user to create the interface of personal profiles, and described profile comprises body weight, height, sex, arm exhibition and body-building professional skill.

In another aspect, this document describes personal computing devices, described personal computing devices comprises: processor, plate carry storer, accelerometer and display; Comprise and can perform with the computer program of the instruction of activity of constructing analytical applications by digital processing device, described activity analysis application comprises: be arranged to the software module receiving acceleration information from described accelerometer, described acceleration information is associated with the body kinematics of user under three dimensions; Be arranged to the software module described equipment being placed in mode of learning, described mode of learning comprises record and carries out the acceleration information of the described user of the activity defined to generate the statistical activity model for described activity; Be arranged to the software module described equipment being placed in normal mode, described normal mode comprises the analysis of described acceleration information applied probability to identify life event, classified by the comparing of motility model with record and identified the multiplicity of described activity described activity; And be arranged to the analysis of described acceleration information applied statistics with the software module of marking to the activity posture of described user.In some embodiments, described equipment also comprises gyroscope, magnetometer or altitude gauge.In some embodiments, described activity analysis application also comprises the software module for receiving data from gyroscope, magnetometer or altitude gauge.In some embodiments, to be suitable for user wearable for described equipment.In further embodiment, described equipment is suitable for can be worn by described user's wrist.In further embodiment, described equipment comprises wearable adapter, and described wearable adapter reversibly can connect from described equipment, to form modular design.In some embodiments, described equipment also comprises biology sensor, is used for measuring the physiological parameter of described user.In further embodiment, described biology sensor is selected from and comprises every group below: heart rate monitor, thermometer, respirometer, glucose monitoring devices, electrolyte sensor and diagometer.In further embodiment, described biology sensor is optical biosensor.In further embodiment, described physiological parameter is selected from and comprises every group below: heart rate, skin temperature, respiratory rate, electrodermal response and aquation.In further embodiment, described application also comprises the software module being arranged to and presenting graphic user interface, and described graphic user interface comprises rest timer.In some embodiments, described equipment also comprises Geographical Location element.In some embodiments, described equipment also comprises wireless communication unit.In further embodiment, described wireless communication unit is bluetooth module or ANT+ module.In some embodiments, be used for comprising the probability analysis that described activity is classified utilizing neural network, context tree weighting, hidden Markov model or its combination.In some embodiments, described scoring comes from the body steadiness of described user, the sports coordination of described user or its combination at least in part.In some embodiments, described scoring comes from comparing of the motility model of described acceleration information and the data genaration by other users at least in part.In some embodiments, described scoring comes from comparing of described acceleration information and the motility model generated by one or more suitable lattice body-building professional person at least in part.In some embodiments, described activity is one-sided weight training activity or bilateral weight training activity.In some embodiments, described application also comprises the software module being arranged to and presenting user interface on the display, described user interface comprise described scoring, described activity, described multiplicity, specific to the message of activity or its combination.In further embodiment, described activity is weight training activity, and the described message specific to activity be selected from comprise below suggestion in every group: weight is too heavy, weight is too light, weight change too many, motion is too fast, health too not steadily, fault, posture be too inharmonious and about the rectification opinion of posture.

In another aspect, this document describes activity analysis platform, described activity analysis platform comprises personal computing devices, described personal computing devices comprises processor, plate carries storer, accelerometer, display and communication device, described equipment is arranged to provides individual activity analytical applications, this individual activity analytical applications comprises: be arranged to the software module receiving acceleration information from described accelerometer, described acceleration information is associated with the body kinematics of user under three dimensions; Be arranged to the software module to acceleration information described in activity analysis server application transport; Described activity analysis platform comprises processor-server, described processor-server is arranged to provides activity analysis server to apply, the application of this activity analysis server comprises: the database of statistical activity model, and described motility model is generated by the acceleration information of the user carrying out the activity defined; Be arranged to the software module receiving acceleration information from described personal computing devices; Be arranged to the analysis of described acceleration information applied probability with identify life event, by with one or more the comparing and described activity classified and identifies the software module of the multiplicity of described activity in described statistical activity model; Be arranged to the analysis of described acceleration information applied statistics with the software module of marking to the activity posture of described user.In some embodiments, described personal computing devices also comprises gyroscope, magnetometer or altitude gauge.In some embodiments, described activity analysis application also comprises the software module for receiving data from gyroscope, magnetometer or altitude gauge.In some embodiments, described platform also comprises at least 100, at least 1000 or at least 10,000 personal computing devices.In some embodiments, described individual activity analytical applications also comprises the software module being arranged to and described personal computing devices being placed in mode of learning, described mode of learning comprises the acceleration information that record carries out the described user of the activity defined, to generate the statistical activity model for described activity.In some embodiments, the database of statistical activity model comprises at least 10, at least 50, at least 100 or at least 500 motility models, and each motility model is associated with specific activity.In some embodiments, each motility model is generated by the average data of the multiple users from the activity carrying out defining.In further embodiment, it is on average the weighted mean of the professional skill level based on each user.In some embodiments, one or more motility model is by the data genaration of the one or more suitable lattice body-building professional person from the activity carrying out defining.In further embodiment, one or more motility model by from the activity correctly not carrying out defining to simulate the data genaration of the suitable lattice body-building professional person of common activity posture problem.In further embodiment, one or more motility model by from the activity correctly carrying out defining with the data genaration of the suitable lattice body-building professional person of illustrated example sexuality posture.In some embodiments, to be suitable for user wearable for described personal computing devices.In further embodiment, described personal computing devices is suitable for can be worn by described user's wrist.In further embodiment, described personal computing devices comprises wearable adapter, and described wearable adapter reversibly can connect from described personal computing devices, to form modular design.In some embodiments, described personal computing devices also comprises biology sensor, is used for measuring the physiological parameter of described user.In further embodiment, described biology sensor is selected from and comprises every group below: heart rate monitor, thermometer, respirometer, glucose monitoring devices, electrolyte sensor and diagometer.In further embodiment, described biology sensor is optical biosensor.In further embodiment, described physiological parameter is selected from and comprises every group below: heart rate, skin temperature, respiratory rate, electrodermal response and aquation.In further embodiment, individual activity analytical applications or the application of described server also comprise the software module being arranged to and presenting graphic user interface, and described graphic user interface comprises timer.In some embodiments, described personal computing devices also comprises Geographical Location element.In some embodiments, described communication device is wireless communication unit.In further embodiment, described wireless communication unit is bluetooth module or ANT+ module.In some embodiments, be used for comprising the probability analysis that described activity is classified utilizing neural network, context tree weighting, hidden Markov model or its combination.In some embodiments, scoring comes from the body steadiness of described user, the sports coordination of described user or its combination at least in part.In some embodiments, described scoring comes from comparing of described acceleration information and the motility model generated by suitable lattice body-building professional person at least in part.In some embodiments, described activity is one-sided weight training activity or bilateral weight training activity.In some embodiments, described individual activity analytical applications or the application of described server also comprise the software module being arranged to and presenting user interface on the display of described personal computing devices, described user interface comprise described scoring, described activity, described multiplicity, specific to the message of activity or its combination.In further embodiment, described activity is weight training activity, and the described message specific to activity be selected from comprise below suggestion in every group: weight is too heavy, weight is too light, weight change too many, motion is too fast, health too not steadily, fault, posture be too inharmonious and about the rectification opinion of posture.In some embodiments, the transmission that described acceleration information is applied to activity analysis server is direct.In some embodiments, the transmission that described acceleration information is applied to activity analysis server is indirectly, and first described data are transferred to local device.In some embodiments, described individual activity analytical applications or the application of described server also comprise the software module being arranged to and presenting and allow described user to create the interface of personal profiles, and described profile comprises body weight, height, sex, arm exhibition and body-building professional skill.

In another aspect, this document describes the non-transient computer-readable recording medium being encoded with and can being performed the instruction carrying out individual activity analysis by processor, described instruction comprises: be arranged to the software module receiving data from the personal computing devices comprising accelerometer, described data comprise the acceleration information from described accelerometer, and described acceleration information is associated with the body kinematics of user under three dimensions; Be arranged to the software module described equipment being placed in mode of learning, described mode of learning comprises the acceleration information that record carries out the described user of the activity defined, to generate the statistical activity model for described activity; Be arranged to the software module described equipment being placed in normal mode, described normal mode comprises the analysis of described acceleration information applied probability to identify life event, classified by the comparing of motility model with record and identified the multiplicity of described activity described activity; And be arranged to the analysis of described acceleration information applied statistics with the software module of marking to the activity posture of described user.In some embodiments, described personal computing devices comprises processor, plate carries storer, accelerometer and display.In some embodiments, described personal computing devices also comprises gyroscope, magnetometer or altitude gauge.In some embodiments, described activity analysis application also comprises the software module being arranged to and receiving data from gyroscope, magnetometer or altitude gauge.In some embodiments, to be suitable for user wearable for described personal computing devices.In further embodiment, described personal computing devices is suitable for can be worn by described user's wrist.In further embodiment, described personal computing devices comprises wearable adapter, and described wearable adapter reversibly can connect from described personal computing devices, to form modular design.In some embodiments, described personal computing devices also comprises biology sensor, is used for measuring the physiological parameter of described user.In further embodiment, described biology sensor is selected from and comprises every group below: heart rate monitor, thermometer, respirometer, glucose monitoring devices, electrolyte sensor and diagometer.In further embodiment, described biology sensor is optical biosensor.In further embodiment, described physiological parameter is selected from and comprises every group below: heart rate, skin temperature, respiratory rate, electrodermal response and aquation.In further embodiment, described medium also comprises the software module being arranged to and presenting graphic user interface, and described graphic user interface comprises rest timer.In some embodiments, described personal computing devices also comprises Geographical Location element.In some embodiments, described personal computing devices also comprises wireless communication unit.In further embodiment, described wireless communication unit is bluetooth module or ANT+ module.In some embodiments, be used for comprising the probability analysis that described activity is classified utilizing neural network, context tree weighting, hidden Markov model or its combination.In some embodiments, described scoring comes from the body steadiness of described user, the sports coordination of described user or its combination at least in part.In some embodiments, described scoring comes from comparing of the motility model of described acceleration information and the data genaration by other users at least in part.In some embodiments, described scoring comes from comparing of described acceleration information and the motility model generated by one or more suitable lattice body-building professional person at least in part.In some embodiments, described activity is one-sided weight training activity or bilateral weight training activity.In some embodiments, described medium also comprises the software module being arranged to and presenting user interface on the display, described user interface comprise described scoring, described activity, described multiplicity, specific to the message of activity or its combination.In further embodiment, described activity is weight training activity, and the described message specific to activity be selected from comprise below suggestion in every group: weight is too heavy, weight is too light, weight change too many, motion is too fast, health too not steadily, fault, posture be too inharmonious and about the rectification opinion of posture.

In another aspect, this document describes the non-transient computer-readable recording medium being encoded with computer program, described computer program comprises and can perform the instruction of applying with activity of constructing Analysis server by processor, described activity analysis server application comprises: the database of statistical activity model, the acceleration information that described motility model is transmitted by the personal computing devices be associated with the user carrying out the exercise defined generates, described acceleration information comprises the data of X-axis, Y-axis and Z axis, and described equipment is in mode of learning; Be arranged to the software module receiving the acceleration information transmitted by the personal computing devices be associated with the user carrying out the exercise defined, described equipment is in normal mode; Be arranged to received acceleration information applied probability analysis with identify life event, by with one or more the comparing and described activity classified and identifies the software module of the multiplicity of described activity in described statistical activity model; Be arranged to received acceleration information applied statistics analysis with the software module of marking to the activity posture of described user.In some embodiments, described personal computing devices comprises processor, plate carries storer, accelerometer and display.Described personal computing devices also comprises gyroscope, magnetometer or altitude gauge.In some embodiments, described activity analysis server application also comprises the software module for receiving data from personal computing devices, and wherein said data transfer to described personal computing devices from accelerometer, gyroscope, magnetometer or altitude gauge.In some embodiments, described individual activity server application is from least 100, at least 1000 or at least 10, and 000 personal computing devices receives data.In some embodiments, described individual activity analytical applications also comprises the software module being arranged to and described personal computing devices being placed in mode of learning, and described mode of learning comprises record and carries out the acceleration information of the described user of the activity defined to generate the statistical activity model for described activity.In some embodiments, the database of described statistical activity model comprises at least 10, at least 50, at least 100 or at least 500 motility models, and each motility model is associated with specific activity.In some embodiments, each motility model is generated by the average data of the multiple users from the activity carrying out defining.In further embodiment, it is on average the weighted mean of the professional skill level based on each user.In some embodiments, one or more motility model is by the data genaration of the one or more suitable lattice body-building professional person from the activity carrying out defining.In further embodiment, one or more motility model by from the activity correctly not carrying out defining to simulate the data genaration of the suitable lattice body-building professional of common activity posture problem.In further embodiment, one or more motility model by from the activity correctly carrying out defining with the data genaration of the suitable lattice body-building professional of illustrated example sexuality posture.In some embodiments, to be suitable for user wearable for described personal computing devices.In further embodiment, described personal computing devices is suitable for can be worn by described user's wrist.In further embodiment, described personal computing devices comprises wearable adapter, and described wearable adapter reversibly can connect from described personal computing devices, to form modular design.In some embodiments, described personal computing devices also comprises biology sensor, is used for measuring the physiological parameter of described user.In further embodiment, described biology sensor is selected from and comprises every group below: heart rate monitor, thermometer, respirometer, glucose monitoring devices, electrolyte sensor and diagometer.In further embodiment, described biology sensor is optical biosensor.In further embodiment, described physiological parameter is selected from and comprises every group below: heart rate, skin temperature, respiratory rate, electrodermal response and aquation.In further embodiment, described individual activity analytical applications or the application of described server also comprise the software module being arranged to and presenting graphic user interface, and described graphic user interface comprises timer.In some embodiments, described personal computing devices also comprises Geographical Location element.In some embodiments, described communication device is wireless communication unit.In further embodiment, described wireless communication unit is bluetooth module or ANT+ module.In some embodiments, be used for comprising the probability analysis that described activity is classified utilizing neural network, context tree weighting, hidden Markov model or its combination.In some embodiments, described scoring comes from the body steadiness of described user, the sports coordination of described user or its combination at least in part.In some embodiments, described scoring comes from comparing of described acceleration information and the motility model generated by suitable lattice body-building professional person at least in part.In some embodiments, described activity is one-sided weight training activity or bilateral weight training activity.In some embodiments, described individual activity analytical applications or the application of described server also comprise the software module being arranged to and presenting user interface on the display of described personal computing devices, described user interface comprise described scoring, described activity, described multiplicity, specific to the message of activity or its combination.In further embodiment, described activity is weight training activity, and the described message specific to activity be selected from comprise below suggestion in every group: weight is too heavy, weight is too light, weight change too many, motion is too fast, health too not steadily, fault, posture be too inharmonious and about the rectification opinion of posture.In some embodiments, the transmission that described acceleration information is applied to activity analysis server is direct.In some embodiments, the transmission that described acceleration information is applied to activity analysis server is indirectly, and first described data are transferred to local device.In some embodiments, described individual activity analytical applications or the application of described server also comprise the software module being arranged to and presenting and allow described user to create the interface of personal profiles, and described profile comprises body weight, height, sex, arm exhibition and body-building professional skill.

Accompanying drawing explanation

Figure 1A is the block diagram of the illustrative embodiments of system.

Figure 1B is the block diagram for radio communication and user's input being integrated into an alternate embodiment of the system in personal data capture device.

Fig. 2 A is the process flow diagram of the method for the analysis to the personal data received by an embodiment of the invention.

Fig. 2 B is for feeding back the process flow diagram be integrated into an alternative approach in the analysis of the personal data received by an embodiment of the invention; And

Fig. 3 is the schematic diagram of the equipment in the system of Figure 1B.

Fig. 4 A is that instruction exercise period strength is on the curve map of the impact of endurance.

Fig. 4 B is the ever-increasing exercise resistance of instruction on the curve map of impact of difficulty carrying out described exercise.

Fig. 5 A is the curve map of the data stream that the system of index map 1B may receive.

If Fig. 5 B is instruction human fatigue, then the curve map that the data stream in the curve map of Fig. 5 A may present.

Fig. 6 is the side view of the illustrative embodiments of the personal computing devices being attached to wrist strap and taking apart from wrist strap.

Fig. 7 shows the illustrative embodiments of instruction personal computing devices, and described personal computing devices is with the image showing the content that equipment shows.

Fig. 8 is the process flow diagram using the illustrative embodiments of the personal computing devices in Fig. 7 to carry out analyzing personal body motion data.

Fig. 9 is the process flow diagram using the exercise posture of illustrative embodiments to user of the personal computing devices in Fig. 7 to mark.

Figure 10 is that the illustrative embodiments of the personal computing devices used in Fig. 7 is to record the process flow diagram of new exercise types.

Embodiment

Physical training is of value to the healthy of individual as everyone knows.But if do not carried out with suitable intensity, amount and duration, then physical training may be unfavorable to the health of individual.In addition, if physical training is not correctly carried out, then unnecessary damage may be there is.Traditional sports equipment can provide some information relevant with the intensity of activity, amount and duration, but this type of information is limited to minority activity.The exercise that private religion is some provides feedback and training; But, for routine work feedback and training may be not too afford and inconvenience.

An advantage of equipment described herein, platform and medium is, they provides for convenient to identify, monitor and record the means of various sports.Utilize its learning ability, add easily and store the type of new sports, for exercise in the future and study.Thus user can select from sports that are far-ranging, that will monitor and follow the tracks of.Further, the physiological parameter of monitor user ' while of when taking exercise, to carry out physical training with the intensity of the best, amount and duration for personal user.Another important advantage is, quantitative comparison is carried out in the performance of user and expert, and provides feedback to promote the raising of effectively study and performance.Generally speaking, equipment described herein, platform and medium can utilize feedback to realize study efficiently, can realize sensitivity monitoring, the storage to physical training and identify easily.

In some embodiments, this document describes personal computing devices, described personal computing devices comprises: processor, plate carry storer, accelerometer, gyroscope and display; Comprise the computer program that can be performed to create by digital processing device the instruction that exercise analysis is applied, the application of described exercise analysis comprises: be arranged to and receive acceleration information and from the software module of gyroscope acceptance angle speed data, described acceleration information and described angular velocity data are associated with the body kinematics of user under three dimensions from accelerometer; Be arranged to the software module described equipment being placed in mode of learning, described mode of learning comprises acceleration information and the angular velocity data that record carries out the user of the exercise defined, to generate the statistics exercise model for this exercise; Be arranged to the software module described equipment being placed in normal mode, described normal mode comprises acceleration information and the analysis of angular velocity data applied probability to identify exercise event, classified by the comparing of exercise model with record and identified the multiplicity of exercise described exercise; And be arranged to described acceleration information and the analysis of described angular velocity data applied statistics with the software module of marking to the exercise posture of user.

In some embodiments, there is also described herein exercise analysis platform, exercise analysis platform comprises: personal computing devices, it comprises processor, plate carries storer, accelerometer, gyroscope, display and communication device, described equipment is arranged to provides individual exercise analysis to apply, this individual exercise analysis application comprises: be arranged to and receive acceleration information and from the software module of gyroscope acceptance angle speed data, described acceleration information and described angular velocity data are associated with the body kinematics of user under three dimensions from accelerometer; Be arranged to the software module to acceleration information described in exercise analysis server application transport and angular velocity data; Exercise analysis platform comprises processor-server, described processor-server is arranged to provides exercise analysis server to apply, the application of this exercise analysis server comprises: the database of statistics exercise model, and described exercise model is generated by the acceleration information of user and angular velocity data carrying out the exercise defined; Be arranged to the software module receiving acceleration information and angular velocity data from described personal computing devices; Be arranged to described acceleration information and the analysis of described angular velocity data applied probability with identify exercise event, by with one or more comparison in statistics exercise model and described exercise is classified and identifies the software module of the multiplicity of described exercise; Be arranged to described acceleration information and the analysis of described angular velocity data applied statistics with the software module of marking to the exercise posture of user.

In some embodiments, there is disclosed herein the non-transient computer-readable recording medium being encoded with instruction, described instruction can be performed to carry out individual exercise analysis by processor, described instruction comprises: be arranged to the software module from comprising accelerometer and gyrostatic personal computing devices reception data, described data comprise from the acceleration information of accelerometer with from gyrostatic angular velocity data, and described acceleration information and described angular velocity data are associated with the body kinematics of user under three dimensions; Be arranged to the software module described equipment being placed in mode of learning, described mode of learning comprises acceleration information and the angular velocity data that record carries out the user of the exercise defined, to generate the statistics exercise model for described exercise; Be arranged to the software module described equipment being placed in normal mode, described normal mode comprises acceleration information and the analysis of angular velocity data applied probability to identify exercise event, classified by the comparing of exercise model with record and identified the multiplicity of described exercise described exercise; And be arranged to described acceleration information and the analysis of described angular velocity data applied statistics with the software module of marking to the exercise posture of described user.

In some embodiments, there is also described herein the non-transient computer-readable recording medium being encoded with computer program, described computer program comprises the instruction that can be performed to create by processor the application of exercise analysis server, described exercise analysis server application comprises: the database of statistics exercise model, the acceleration information that exercise model is transmitted by the personal computing devices be associated with the user carrying out the exercise defined and angular velocity data generate, described acceleration information and described angular velocity data comprise X-axis separately, the data of Y-axis and Z axis, described equipment is in mode of learning, be arranged to the software module receiving acceleration information and the angular velocity data transmitted by the personal computing devices be associated with the user carrying out the exercise defined, described equipment is in normal mode, be arranged to and received acceleration information and angular velocity data applied statistics analyzed identify exercise event, by with one or more comparison added up in exercise model and described exercise is classified and identifies the software module of the multiplicity of described exercise, be arranged to received acceleration information and the analysis of angular velocity data applied statistics with the software module of marking to the exercise posture of user.

In some embodiments, there is also described herein personal computing devices, described personal computing devices comprises: processor, plate carry storer, accelerometer and display; Comprise and can perform with the computer program of the instruction of activity of constructing analytical applications by digital processing device, described activity analysis application comprises: be arranged to the software module receiving acceleration information from accelerometer, described acceleration information is associated with the body kinematics of user under three dimensions; Be arranged to the software module described equipment being placed in mode of learning, described mode of learning comprises record and carries out the acceleration information of the user of the activity defined to generate the statistical activity model for described activity; Be arranged to the software module described equipment being placed in normal mode, described normal mode comprises the analysis of acceleration information applied probability to identify life event, classified by the comparing of motility model with record and identified the multiplicity of described activity described activity; And be arranged to the analysis of acceleration information applied statistics with the software module of marking to the activity posture of user.

In some embodiments, there is also described herein activity analysis platform, described activity analysis platform comprises: personal computing devices, it comprises: processor, plate carry storer, accelerometer, display and communication device, described equipment is arranged to provides individual activity analytical applications, this individual activity analytical applications comprises: be arranged to the software module receiving acceleration information from described accelerometer, described acceleration information is associated with the body kinematics of user under three dimensions; Be arranged to the software module to acceleration information described in activity analysis server application transport; Described activity analysis platform comprises processor-server, described processor-server is arranged to provides activity analysis server to apply, the application of this activity analysis server comprises: the database of statistical activity model, and described motility model is generated by the acceleration information of the user carrying out the activity defined; Be arranged to the software module receiving acceleration information from personal computing devices; Be arranged to the analysis of acceleration information applied probability with identify life event, by with one or more the comparing and described activity classified and identifies the software module of the multiplicity of described activity in statistical activity model; Be arranged to the analysis of acceleration information applied statistics with the software module of marking to the activity posture of user.

In some embodiments, there is also described herein the non-transient computer-readable recording medium being encoded with and can being performed the instruction carrying out individual activity analysis by processor, described instruction comprises: be arranged to the software module receiving data from the personal computing devices comprising accelerometer, described data comprise the acceleration information from accelerometer, and described acceleration information is associated with the body kinematics of user under three dimensions; Be arranged to the software module described equipment being placed in mode of learning, described mode of learning comprises record and carries out the acceleration information of the user of the activity defined to generate the statistical activity model for described activity; Be arranged to the software module described equipment being placed in normal mode, described normal mode comprises the analysis of acceleration information applied probability to identify life event, classified by the comparing of motility model with record and identified the multiplicity of described activity described activity; And be arranged to the analysis of acceleration information applied statistics with the software module of marking to the activity posture of user.

In some embodiments, there is also described herein the non-transient computer-readable recording medium being encoded with computer program, described computer program comprises and can perform the instruction of applying with activity of constructing Analysis server by processor, the application of this activity analysis server comprises: the database of statistical activity model, the acceleration information that motility model is transmitted by the personal computing devices be associated with the user carrying out the exercise defined generates, described acceleration information comprises the data of X-axis, Y-axis and Z axis, and described equipment is in mode of learning; Be arranged to the software module receiving the acceleration information transmitted by the personal computing devices be associated with the user carrying out the exercise defined, described equipment is in normal mode; Be arranged to received acceleration information applied probability analysis with identify life event, by with one or more the comparing and described activity classified and identifies the software module of the multiplicity of described activity in statistical activity model; Be arranged to received acceleration information applied statistics analysis with the software module of marking to the activity posture of user.

some term

Unless otherwise defined, all terms used herein have usual the understood identical meanings with those skilled in the art.As in this specification and the appended claims use, singulative " ", " one " and " being somebody's turn to do " comprise plural reference, unless the context clearly indicates otherwise."and/or" is comprised to any intention of quoting of "or" herein, except as otherwise noted.

general introduction

The present invention relates to and use personal computing devices to the statistical study of the three-dimensional caught by motion sensor (3D) body motion data.The individual exercise analysis application of this personal computing devices be arranged to collect catch from accelerometer and gyroscope 3D exercise data, perform statistical study to such data.This equipment is also arranged to present over the display tempers relevant information and the physiologic information of user.Further, present invention incorporates statistical model to identify the new exercise undertaken by user.The present invention be also incorporated with for by the exercise undertaken by user and record, analytical approach that the exercise undertaken by suitable lattice body-building expert compares, to promote accurately and efficiently to learn.

personal computing devices

In some embodiments, equipment described herein, platform and medium comprise personal computing devices.In some embodiments, personal computing devices comprises processor, storer, accelerometer and display.In some embodiments, the acceleration under accelerometer measures Spatial Dimension, under two Spatial Dimensions or under three Spatial Dimensions and/or under a time dimension, wherein for any single dimension, has forward and negative sense.In some embodiments, personal computing devices comprises accelerometer, gyroscope, magnetometer or altitude gauge.In some embodiments, the orientation information under gyroscope survey Spatial Dimension, under two Spatial Dimensions or under three Spatial Dimensions and/or under a time dimension, wherein for any single dimension, has forward and negative sense.In some embodiments, what processor comprised in the following is one or more: digital signal processor, digital processing unit, microprocessor or special IC (ASIC).

In some embodiments, personal computing devices comprises the display on equipment.In some embodiments, the color of display, font, image size, contrast or content are that user selects.In some embodiments, personal computing devices comprises audio indicator alternatively.In further embodiment, select the content of the display on equipment to export as audio frequency by user.

In some embodiments, personal computing devices is that user is wearable.In further embodiment, personal computing devices can be worn by user's wrist.In other embodiments, personal computing devices can be attached to any skin area on health.In some embodiments, described equipment comprises wearable adapter, and this wearable adapter reversibly can connect from this equipment, to form modular design.In some embodiments, personal computing devices can around shoulder, ear, neck, finger, palm, ankle, chest, arm, waist, leg, pin or torso-worn.In some embodiments, described equipment comprises the adapter allowing this equipment to be reversibly connected to body-building apparatus, exercising apparatus, physical education facilities etc.In further embodiment, described equipment is attached to or is reversibly connected to dumbbell, barbell, rowing machine, boat pedal, baseball bat, golf clubs, tennis racket, racket, table tennis bat, boxing glove, floorboard, handle, gloves, dress, footwear, waistband, seat, handrail, mat etc.In other embodiments, described equipment is reversibly connected to mobile device, computing machine, GPS, iPad, usb driver, printer, scanner, TV, server, automobile, intelligent watch, Google's glasses, iPod, game machine, projector, camera or similar electronic equipment.

In some embodiments, described equipment also comprises biology sensor, is used for measuring the physiological parameter of user.In further embodiment, biology sensor is optical biosensor, electrically biology sensor, magnetic biosensor, electro permanent magnetic biology sensor, chemical biosensor, electrochemica biological sensor, UV optical biosensor, pressure biology sensor, speed biology sensor, sound biology sensor, calorimetric biosensor or mechanical type biology sensor.In further embodiment, biology sensor comprises heart rate monitor, thermometer, respirometer, blood sugar monitoring instrument, electrolyte sensor, diagometer, pre ure tra ducer, blood oxygen transducer, body fat sensor, muscle sensor, EMG electrode, EEG sensor, ECG electrode, body aquation sensor etc.In some embodiments, physiological parameter comprises heart rate, skin temperature, respiratory rate, pulse, electrodermal response, aquation, blood oxygen level, blood sugar level, body fat rate, muscular fatigue degree, EMG, EEG, ECG etc.

With reference to figure 6, in certain embodiments, personal computing devices is attached to wrist strap via wearable adapter or takes apart from wrist strap.

With reference to figure 7, in certain embodiments, personal computing devices is attached to wrist strap, and shows the example images of the display on equipment.In this particular embodiment, display on equipment shows the greeting " free Home Coach (FreeCoachHome) " of device start, and exercise posture is recorded as " routine 1 (Routine1) " when user is just carrying out corresponding exercise.Display on equipment shows the body weight of user's input alternatively, as a part for user profiles.When user performs physical exercise, display on equipment illustrates the exercise multiplicity (REPS of user alternatively, exerciserepetitionnumber) and the physiological parameter of user, such as with the heart rate of heartbeat number of times (BPM, beatperminute) per minute.

In some embodiments, described equipment also comprises the software module being arranged to and presenting graphic user interface, and this graphic user interface comprises rest timer.In further embodiment, rest timer is based on physiological parameter, and described physiological parameter is selected from heart rate, skin temperature, blood pressure, blood oxygen level, blood sugar level, respiratory rate, body hydration level, electrodermal response, body fat rate, EMG signal, EEG signal, ECG signal, muscular fatigue degree etc.In other embodiments, rest timer is determined by duration of exercise, the calorie burnt, exercise multiplicity, exercise scoring, poor form or other exercise dependent events.

In some embodiments, described equipment also comprises Geographical Location element, and wherein Geographical Location element identifies the geographic position of personal computing devices.In further embodiment, geographic position comprises height, height above sea level, latitude, longitude, coordinate, atmospheric pressure etc.

In some embodiments, described equipment also comprises wireless communication unit, and wherein this element allows to apply with body-building apparatus, computing machine, exercise analysis server, another person's computing equipment, physical education facilities etc. carry out radio communication.In further embodiment, wireless communication unit is bluetooth module, ANT+ module, Wi-Fi module, IEEE802.15.4 microchip, purple honeybee (ZigBee) module, Wireless USB, IrDA module, wound wave (ZWave) module, wireless network adapter, wireless Internet card, body region mixed-media network modules mixed-media, near-field communication etc.

the application of individual's exercise analysis

In some embodiments, equipment described herein, platform and medium comprise the application of individual exercise analysis or its use.In some embodiments, individual exercise analysis application comprises the software module for receiving the data be associated with the body kinematics of user under three dimensions.In further embodiment, the data be associated with the body kinematics of user under three dimensions comprise acceleration information and/or angular velocity data.In other embodiment, the data receiver be associated with the body kinematics of user under three dimensions since accelerometer or gyroscope select one or more.In other embodiments, the data be associated with the body kinematics of user under three dimensions are acceleration informations.In further embodiment, the data receiver be associated with the body kinematics of user under three dimensions is from one or more accelerometer.In some embodiments, acceleration information (wherein for any single dimension, there is forward and negative sense) under acceleration information comprises a Spatial Dimension, under two Spatial Dimensions or under three Spatial Dimensions and/or under a time dimension or its combination.In some embodiments, orientation information (for any single dimension, there is forward and negative sense) under angular velocity data comprises a Spatial Dimension, under two Spatial Dimensions or under three Spatial Dimensions and/or under a time dimension or its combination.In some embodiments, acceleration information and angular velocity data are 3 × 3 vectors.In other embodiments, acceleration information and angular velocity data are four dimensional vectors.In other embodiment, the data receiver be associated with the body kinematics of user under three dimensions is from pressure transducer, GPS, timer, speed pickup, vibration transducer or thermometer.In some embodiments, the data be associated with the body kinematics of user under three dimensions comprise one dimension, two-dimentional or three-dimensional distance, displacement, acceleration, angular velocity, linear momentum, speed, coordinate, geo-location, power, moment of torsion, radius, circumference, height above sea level, duration, pressure etc.In further embodiment, the data be associated with the body kinematics of user under three dimensions comprise to one dimension, two dimension or the mathematics manipulation of distance, displacement, acceleration, angular velocity, linear momentum, speed, coordinate, geo-location, power, moment of torsion, radius, circumference, height above sea level, duration, pressure etc. of three-dimensional or statistical treatment.In some embodiments, also relevant with exercise environment with the data that the body kinematics of user under three dimensions is associated, described exercise environment comprises atmospheric pressure, water resistance, windage resistance, hydraulic pressure, wind speed, water speed, gravity horizontal or temperature.

In some embodiments, individual exercise analysis application comprises the software module being arranged to and personal computing devices being placed in mode of learning.In some embodiments, mode of learning comprises the data recording and be associated with the body kinematics of user under a dimension, two dimensions or three dimensions carrying out the exercise defined.In further embodiment, the data be associated with the body kinematics of user under three dimensions are acceleration information and/or the angular velocity data of the user carrying out the exercise defined, to generate the statistics exercise model for described exercise.In some embodiments, user is one or more in the body-building professional person of suitable lattice, coach, private religion, expert, sportsman, professional athlete, robot etc.In some embodiments, exercise is the exercise that heart exercise, weight training, intensity exercise, flexibility exercises or technical ability are relevant.In further embodiment, exercise is one-sided weight training, bilateral weight training, push-up exercise, flight is taken exercise, dumbbell exercise, drop-down exercise, draw to lift and take exercise, barbell is taken exercise, pull-up is taken exercise, baseball is taken exercise, sit-up exercise, curling exercise, flat support is taken exercise, picked exercise, elect and take exercise, under push away exercise, floor press is taken exercise, tennis is taken exercise, golf exercise, boat is taken exercise, shuttlecock is taken exercise, Tennis Exercise, swimming exercise, boxing is taken exercise, bowling is taken exercise, dance and take exercise, yoga exercise, pilates is taken exercise, rowing exercise, take exercise by running, jogging exercise, take exercise on foot, rock-climbing is taken exercise, skating is taken exercise, bicycle sport, hockey is taken exercise, fencing is taken exercise, surfing is taken exercise, archery is taken exercise, to ride exercise, shooting is taken exercise etc.In further embodiment, the statistics exercise model of the exercise of definition generates separately based on exercise types, age, body weight, height, sex, arm exhibition, multiplicity or this type of information.

In some embodiments, each exercise model is generated by the average data of the one or more users from the exercise carrying out defining.In further embodiment, average data is the weighted mean data of the professional skill level based on each user.In some embodiments, one or more exercise model is by the data genaration of the one or more suitable lattice body-building professional person from the exercise carrying out defining.In some embodiments, one or more exercise model by from the exercise correctly not carrying out defining to simulate the data genaration of the suitable lattice body-building professional person of common exercise posture problem.In other embodiments, one or more exercise model is by the data genaration of suitable lattice body-building professional person of tempering posture from the exercise correctly carrying out defining with illustrated example.In other embodiments, each exercise model is generated by the average data of the sole user from the exercise carrying out defining with multiple multiplicity.In further embodiment, statistical model is generated by the 3D body kinematics of the user carrying out the exercise defined.

In some embodiments, the application of individual's exercise analysis also comprises the software module being arranged to and described equipment being placed in normal mode, normal mode comprise to three dimensional body move the market demand probability analysis that is associated with identify exercise types, by with comparing of exercise model of recording and exercise types is classified and identifies the multiplicity of exercise.In some embodiments, three dimensional body motion is the original motion related data of collecting from personal computing devices.In other embodiments, before applied probability analysis, based on the raw data of collecting from motion sensor, pre-service is carried out to 3D body kinematics related data.In further embodiment, it is one or more that pre-service comprises in the following: space, being averaging of time or frequency dependence, quantize, denoising, smoothing, linear or nonlinear fitting, filtering, weighting, cut position, deletion, change, take advantage of, subtract, remove, interpolation, differentiate, round up, recombinate, extract square root, exponentiation etc.In other embodiment, pre-service comprises mathematical operation to raw data or statistical calculation, comprise calculate scale, z-scoring, quantize, PCA analyzes (principal component analysis (PCA)), deducts the average of raw data, the standard deviation etc. divided by raw data.

In some embodiments, be used for comprising the probability analysis that exercise is classified utilizing neural network, context tree weighting, hidden Markov (Markov) model, dynamic system, principal component analysis (PCA), k-mean cluster, dynamic bayesian network, mixture model, regression model, Markov random field, condition random field, template matches, dynamic probability graphical model, K-arest neighbors model, patent model of cognition, Statistical learning model, machine learning model or its combination.In some embodiments, the input of probability analysis comprises the undressed body motion data of the user of the exercise carrying out one or more definition under a dimension, under two dimensions or under three dimensions.In further embodiment, the input of probability analysis comprise the user of the exercise carrying out one or more definition under a dimension, under two dimensions or under three dimensions through pretreated body motion data.In further embodiment, pre-service is undertaken by mathematical operation or statistical calculation.In some embodiments, the input of probability analysis comprises the exercise model of one or more record.In some embodiments, the output of probability analysis comprises the vector etc. of probability, the vector of probability, conspicuousness, the vector of conspicuousness, p value, the vector of p value, evaluated error, evaluated error.In further embodiment, output valve is more than or equal to 0 and is less than or equal to 1.In further embodiment, the output of probability analysis have fixing and.In other embodiment, the output of probability analysis and be 1.

In some embodiments, the application of individual exercise analysis also comprises and being arranged to the market demand relative method of 3D body kinematics with the software module of marking to the exercise posture of user.In further embodiment, scoring comprises average score, the highest scoring of individual, individual minimum scoring, the scoring distribution in a period of time, the distribution of the scoring in multiplicity or this type of combination.Relative method comprise the difference of two squares and, statistical discrepancy, root-mean-square-deviation, root-mean-square-deviation and, root mean square and, return, Mahalanobis (Mahalanobis) distance or this type of combination.In further embodiment, use is selected from the exercise posture of the letter scale in the list of A, B, C, D, E and F to user and marks.In other embodiments, the exercise posture of the centile of usable range between 100 hundredths to 0 hundredths to user is marked.In other embodiments, the exercise posture of the numerical grade of usable range between 10 to 0,5 to 0 or 4 to 0 to user is marked.In some embodiments, scoring comes from raising within a period of time or multiplicity of the body steadiness of user, the sports coordination of user, user or its combination at least in part.In some embodiments, scoring comes from comparing of the data of the 3D body kinematics of user and the exercise model generated by different user or the exercise model that generated by the mean value of the data of at least two other users at least in part.In further embodiment, different user or other users are the body-building professional person of one or more suitable lattice, coach, private religion, expert, sportsman, professional athlete, robot etc.

In some embodiments, described application also comprises the software module being arranged to and presenting user interface, and described user interface allows mutual via the user-equipment of input equipment.In further embodiment, input equipment comprises touch-screen, button, button, rolling, mouse, keyboard, sensing equipment, telepilot, microphone, motion sensor, eye movement sensor, temperature sensor, optical sensor or pressure transducer.In further embodiment, comprise touch alternately, click, vibrate, shake, touch, highlighted, draw circle, sketch outline, gesture, sensing, slip, pressing, eye movement or intersection.In some embodiments, user interface allows user to create or selects for the content shown on equipment, equipment mode, rest timer, via the immediate feedback of sound, light or vibration, equipment Alignment, error reporting, error correcting, tempers relevant prompting, the prompting that physiological data is relevant, or its combination.In further embodiment, the immediate feedback via sound, light or vibration comprises the feedback to the performance that the physiological data of user or the exercise of user are correlated with.In some embodiments, on equipment, display comprises display scoring, exercise types, repeat number, muscular fatigue degree, duration of exercise, the message specific to exercise, user's physiological data, message etc. specific to equipment.In further embodiment, graphic user interface allows user to utilize one or more mathematical operation or statistical calculation to make correction to exercise relevant information and/or activity related information.In further embodiment, activity related information comprises the derivative information of Activity Type, multiplicity, activity log, scoring, average score, average duration, average heavy burden, total duration, overall score, minimum or the highest scoring, scoring daily record, heavy burden, duration or any activity.In further embodiment, use tempering the correction of relevant information to upgrade statistical study or probability analysis.

In some embodiments, exercise is weight training, and comprises specific to the message of taking exercise: the time of cost, multiplicity, weight are too heavy, weight is too light, weight change too many, motion is too fast, health too not steadily, posture is too incorrect, posture is too inharmonious, the exercise number of times that stores and about the rectification opinion of tempering posture.In some embodiments, the message specific to equipment comprises: bluetooth connects, bluetooth disconnects, the total exercise number of times stored, newly-increased exercise types, the exercise types of deletion, exercise types mistake, storage space are low, battery electric quantity notice, the geo-location detected, reset timer start, the stopping of reset timer, geo-location mistake, the environment detected, environment error or this type of combination.

Fig. 3 is the schematic diagram of the use of system 110.System 110 is worn on arm 304 by user 303.User 303 positive carry bears a heavy burden 301, is just utilizing this heavy burden 301 to carry out exercise 302.When carrying out exercise 302, the position of system 110 on arm 214 changes.Data about the position of user 303 and arm 304 can be detected by user data receiver 101.The analysis that microprocessor 102 can utilize software 104 to carry out these data, to determine exercise 302.The exercise 302 carried out can be stored in storer 103, be sent to communication unit 105 and/or utilize display 106 to present to user 303.User 303 can input data 117 then, microprocessor 102 by according to software 104 usage data 117 to adjust computations in the future.Analyze 210 and can also comprise the set calculating multiplicity and different exercise.

Fig. 4 A is the curve map of the strength level that indicating user 303 can be paid when carrying out exercise 302.Which show and which kind of degree of fatigue can be set to user 303.

Fig. 4 B be the exercise resistance experienced of indicating user 303 or bear a heavy burden 301 how to affect perform physical exercise 302 the curve map of difficulty.

Fig. 5 A show when user 303 perform physical exercise when not tired 302 or when with lower resistance or with low heavy burden 301 perform physical exercise 302 time, system 100 is by the data stream received by receiver 101.

Fig. 5 B show to perform physical exercise when user 303 is in fatigue 302 or when with high-drag or with height bear a heavy burden 301 perform physical exercise 302 time, system 100 is by the data stream received by receiver 101.Fluctuation in this data stream is caused by muscle tremors.When there is micro-tearing in muscle, there is muscle tremors; These are torn and cause of flaccid muscles, and muscle flexing that this is of flaccid muscles is increased very is soon offset.When starting tired, or when resistance increases, this slightly tears and becomes more general and can mix, thus the fluctuation causing data centralization larger.

Data fluctuations between Fig. 5 A and Fig. 5 B is used for estimating the heavy burden 301 that user 303 is just using in exercise 203 by system 100.The present invention depends on the data that obtain when exercise period starts or calculates fluctuation from the data in previous exercise stage and thus estimated resistance.

In some embodiments, the application of individual exercise analysis comprise be arranged to or from exercise analysis server application transport or the software module receiving the data be associated with the 3D body kinematics of the user carrying out the exercise defined.In further embodiment, transmission or reception are direct.In other embodiments, transmission or reception are indirectly, and wherein first data are transferred to digital device.In further embodiment, digital device is computing machine, mobile device, online account, online database, digital storage media, server, hub, hard disk drive, usb driver, cloud storage space etc.

In some embodiments, individual exercise analysis application also comprises the software module being arranged to and presenting and allow user to create the interface of personal profiles.In further embodiment, profile comprise body weight, height, the age, sex, arm exhibition, body-building professional skill, exercise goal, scoring target, to wear the preference of described equipment, exercise journal, scoring record, to the statistical study etc. of tempering relevant information.

In some embodiments, server application comprise be arranged to the 3D body motion data applied probability analysis of the user of the exercise defined with identify exercise event, by with one or more comparison added up in exercise model and this exercise is classified and identifies the software module of the multiplicity of taking exercise.In further embodiment, 3D body motion data comprises acceleration information and angular velocity data.

In some embodiments, described application comprises and being arranged to acceleration information and the analysis of angular velocity data applied statistics with the software module of marking to the exercise posture of user.In further embodiment, scoring comprises average score, the highest scoring of individual, individual minimum scoring, the scoring distribution in a period of time, the distribution of the scoring in multiplicity or this type of combination.Relative method comprise the difference of two squares and, root-mean-square-deviation, root-mean-square-deviation and, root mean square and, return, Mahalanobis generalised distance or this type of combination.In further embodiment, use is selected from the exercise posture of the letter scale in the list of A, B, C, D, E and F to user and marks.In other embodiments, the exercise posture of the centile of usable range between 100 hundredths to 0 hundredths to user is marked.In other embodiments, the exercise posture of the numerical grade of usable range between 10 to 0,5 to 0 or 4 to 0 to user is marked.In some embodiments, scoring comes from raising within a period of time or multiplicity of the body steadiness of user, the sports coordination of user, user or its combination at least in part.In some embodiments, scoring comes from comparing of the data of the 3D body kinematics of user and the exercise model generated by different user or the exercise model that generated by the mean value of the data of at least two other users at least in part.In further embodiment, different user or other users are the body-building professional person of one or more suitable lattice, coach, private religion, expert, sportsman, professional athlete, robot etc.

With reference to figure 8, show the process flow diagram using the illustrative embodiments of the personal computing devices in Fig. 7 to carry out analyzing personal exercise data.When user carries out with a certain multiplicity the exercise defined, 3D body motion data (that is, 3D acceleration information and/or 3D angular velocity data) is read to individual exercise analysis application 800 from motion sensor.Motion sensor comprises accelerometer and gyroscope alternatively.Draw and select the input 810 that the feature of the original motion data is applied as individual exercise analysis alternatively.Before such input being fed in Statistic analysis models 831,832,833,834 or 835, alternatively pre-service 820 is carried out to it.Pre-service 820 comprises alternatively by deducting average and calculating scale or z-scoring divided by standard deviation.Or, PCA (principal component analysis (PCA)) 820 is carried out to remove linear correlation to original input.In this particular embodiment, statistical model is selected from neural network 831 or 835, context tree weighting 832, hidden Markov model 833 or 834 or their combination alternatively, to estimate carried out exercise and/or multiplicity.In addition, in this embodiment, the prediction probability be associated with estimated exercise and estimated multiplicity 841 or 842 is obtained from statistical model 831,832 or 833.In this particular embodiment, prediction probability is the vector of probability.The exercise posture estimated generates based on the prediction probability be associated with estimated exercise and estimated multiplicity 841 or 842.Alternatively, the exercise posture further estimated by process is to make carried out exercise and multiplicity smoothing 851 and to extract it.When detect between carried out exercise and the exercise of record mate 861 time, carry out posture analysis 880 by comparing carried out exercise data with the exercise of recording, and relatively calculate posture scoring 890 based on this.Alternatively, the prediction probability be only associated with the exercise 844 or 845 estimated is obtained from statistical model 833,834 or 835.The exercise posture estimated generates based on the prediction probability be associated with the exercise 844 or 845 estimated.Alternatively, further the exercise posture estimated of process to make carried out exercise and multiplicity smoothing 855 and to extract it.When detect between carried out exercise and the exercise of record mate 860 time, calculate multiplicity 870, and carry out posture analysis 880 by comparing carried out exercise data with the exercise of recording, and relatively calculate posture scoring 890 based on this.Alternatively, make comparisons 890 via mathematical operation, mathematical operation comprise root-mean-square-deviation or root mean square and.The information 899 of exercise types, multiplicity and the posture scoring carried out is shown to user.

Fig. 9 is the process flow diagram using the exercise posture of illustrative embodiments to user of the personal computing devices in Fig. 7 to mark.In this particular embodiment, user repeats the exercise of definition.Use 3D body motion data that such as obtain from the motion sensor such as accelerometer and gyroscope 900, that be associated with exercise types, multiplicity and confidence level as input.Analyze for kinetic stability scoring 910 to input and/or input is separated into different multiplicity 920.In addition, in this embodiment, the multiplicity of one or more separation and the exercise model of record are compared 932, and compare generation similarity score 940 based on this.Alternatively, carry out assessing the part as marking to the similarity 931 of different multiplicity, and mark with similarity score 940 and stability alternatively and 910 carry out combining to generate finally marking 950.Final scoring comprises the scoring of polymerization posture and/or the scoring of single posture that are shown to user alternatively.Alternatively, in this embodiment, when similarity score cannot be calculated, poor form 940 detected, and show error message instead of scoring 950.

In some embodiments, the application of individual's exercise analysis also comprises the software module being arranged to and described equipment being placed in calibration mode, calibration mode comprises and to move the market demand probability analysis be associated to one or more three dimensional body of specific user, relies on parameter with the user identified in probability model.In some embodiments, three dimensional body motion is the original motion related data of collecting from personal computing devices.In other embodiments, based on the raw data of collecting from motion sensor before applied probability is analyzed, pre-service is carried out to 3D body kinematics related data.In further embodiment, it is one or more that pre-service comprises in the following: space, being averaging of time or frequency dependence, quantize, denoising, smoothing, linear or nonlinear fitting, filtering, weighting, cut position, deletion, change, take advantage of, subtract, remove, interpolation, differentiate, round up, recombinate, extract square root, exponentiation etc.In other embodiment, pre-service comprises mathematical operation to raw data or statistical calculation, comprise calculate scale, z-scoring, quantize, PCA analyzes (principal component analysis (PCA)), deducts the average of raw data, the standard deviation etc. divided by raw data.

exercise analysis server is applied

In some embodiments, equipment described herein, platform and medium comprise the application of exercise analysis server or its use.In some embodiments, server application comprises the database of statistics exercise model.In further embodiment, database comprises at least 1, at least 2, at least 5, at least 8, at least 10, at least 20, at least 40, at least 50, at least 80, at least 100, at least 150, at least 250, at least 200, at least 300, at least 400 or at least 500 exercise model, and wherein each model is associated with specific exercise.In further embodiment, open up with exercise types, user's sex, age of user, user's weight, user's height, user's arm in a database, multiplicity, duration of exercise or this type of combination store specific exercise model explicitly.In some embodiments, each exercise model is generated by the average data of the multiple users from the exercise carrying out defining.In further embodiment, average data is the weighted mean data of the professional skill level based on each user.In some embodiments, one or more exercise model is by the data genaration of the one or more suitable lattice body-building professional person from the exercise carrying out defining.In some embodiments, one or more exercise model by from the exercise correctly not carrying out defining to simulate the data genaration of the suitable lattice body-building professional person of common exercise posture problem.In other embodiments, one or more exercise model is by the data genaration of suitable lattice body-building professional person of tempering posture from the exercise correctly carrying out defining with illustrated example.In other embodiments, each exercise model is generated by the average data of the sole user from the exercise carrying out defining with different multiplicity.In further embodiment, each exercise model generates by carrying out the one dimension of user of the exercise defined, two dimension or three-dimensional body motion data.In further embodiment, the body motion data of carrying out the user of the exercise defined be received from accelerometer acceleration information or be received from gyrostatic angular velocity data.In other embodiment, body motion data is received from pressure transducer, GPS, timer or thermometer.In some embodiments, the 3D body kinematics related data of user comprises one dimension, two dimension or three-dimensional distance, displacement, acceleration, angular velocity, linear momentum, speed, coordinate, geo-location, power, moment of torsion, radius, circumference, highly.In some embodiments, the data of reception are also relevant with exercise environment, and described exercise environment comprises atmospheric pressure, hydraulic pressure, wind speed, water speed, gravity horizontal or temperature.

In some embodiments, the application of exercise analysis server comprises the software module being arranged to and carrying out the 3D body kinematics related data of the user of the exercise defined from personal computing devices reception.In further embodiment, server application receives the 3D body kinematics related data of carrying out the user of the exercise defined from least 5, at least 8, at least 10, at least 20, at least 30, at least 40, at least 50, at least 80, at least 100, at least 200, at least 500, at least 1000, at least 5000, at least 10000 or at least 20000 personal computing devices.

In some embodiments, server application comprise be arranged to the 3D body motion data applied probability analysis of the user of the exercise defined with identify exercise event, by with one or more comparison added up in exercise model and exercise types is classified and/or identifies the software module of multiplicity of exercise.In some embodiments, server is applied to comprise and is arranged to the analysis of 3D body motion data applied statistics with the software module of marking to the exercise posture of user.In further embodiment, the data of 3D body kinematics comprise acceleration information and angular velocity data.In further embodiment, the data of 3D body kinematics comprise one dimension, two dimension or three-dimensional distance, displacement, acceleration, angular velocity, linear momentum, speed, coordinate, geo-location, power, moment of torsion, radius, circumference, highly.In further embodiment, the 3D body kinematics related data of user comprise to one dimension, two dimension or three-dimensional distance, displacement, acceleration, angular velocity, linear momentum, speed, coordinate, geo-location, power, moment of torsion, radius, circumference, highly, the duration, the mathematics manipulation of pressure etc. or statistical treatment.In some embodiments, received data are also relevant with exercise environment, and described exercise environment comprises atmospheric pressure, hydraulic pressure, wind speed, water speed, gravity horizontal or temperature.

In some embodiments, the application of exercise analysis server also comprises the software module being arranged to and presenting the interface allowing user's establishment, amendment, deletion or preserve personal profiles.In further embodiment, profile comprise body weight, height, the age, sex, arm exhibition, body-building professional skill, to the preference etc. wearing described equipment.

Figure 10 is that the illustrative embodiments of the personal computing devices used in Fig. 7 is to record the process flow diagram of new exercise types.In this particular embodiment, user enters new exercise mode 1000 and adorns oneself with personal computing devices and carries out new exercise with a certain multiplicity.By accelerometer and gyroscope sense movement data and read to exercise analysis application.Alternatively, when the confidence level of data of collecting is greater than pre-established threshold 1010, stores motion sensor data and via radio communication new exercise be added into the database 1021 in the application of exercise analysis server.In addition, in this embodiment, when the confidence level of exercise data is less than pre-established threshold 1010 alternatively, new multiplicity 1020 is pointed out to user.User starts the same exercise of repetition 1030 to generate new exercise data 1040.Alternatively, pre-service 1050 is carried out with by detecting new the value of the confidence and itself and threshold being compared 1010 and reenter new exercise and detect and circulate to the new exercise data carrying out sensor.

Figure 1A is the block diagram of the illustrative embodiments of system 100.Example devices such as can comprise the computing machine with internal hardware configuration, and described hardware configuration comprises microprocessor 102 and storer 103.Microprocessor 102 can be the controller of the operation for controlling portable computing device 100.Microprocessor 102 is such as connected to storer 103 by memory bus.Storer 103 is FLASH memory, random access memory (RAM), ROM (read-only memory) (ROM) or any other suitable memory device alternatively.Storer 103 can store the data and programmed instruction that are used by microprocessor 102.Programmed instruction can be with the form of software 104.Software 104 can completely or partially reside in microprocessor 102 or storer 103.User data receiver 101 can be coupled with microprocessor 102.When reading data from user data receiver 101, microprocessor 102 can from storer 103 reading software 104 to perform analysis to data.Analysis can be stored in storer 103 or be sent to communication unit 105, and wherein communication unit 105 can to another equipment sending data.Described analysis and/or display 106 can be utilized to present to user from the raw data of user data receiver 101.

Figure 1B is the block diagram of an embodiment of system, and wherein system 110 can be carried out radio communication 115 and be received the input data 117 from user.

Fig. 2 is flow process Figure 200 of the method for analysis for the personal data 205 received an embodiment of the use 202 by equipment 100.Analyze 210 by have on the device software 104, the microprocessor 102 of this equipment, generate based on described data.Then utilize display 106, to user, display feedback 215 is shown.Then communication unit 105 can be utilized to all information in utility appliance 220 transmission memory 103.

Fig. 2 B is the process flow diagram 201 of the method for analysis for the personal data 205 received an embodiment of the use 202 by equipment 110.After display feedback 215 is shown, equipment 110 is collected user input data 117 and is improved feedback 255 to analysis adjustment.The further analysis 250 undertaken by equipment 110 can reflect the adjustment inputting 255 based on user.

exercise model

In some embodiments, each exercise model is associated with specific physical training.In further embodiment, specific exercise model and exercise types, user's sex, age of user, user's weight, user's height, user's arm are opened up, multiplicity, duration of exercise or this type of combination store in a database explicitly.In some embodiments, add in the database that exercise analysis server is applied or individual exercise analysis is applied, revise, delete exercise model.In some embodiments, each exercise model is generated by the average data of the multiple users from the exercise carrying out defining.In further embodiment, average data is the weighted mean data of the professional skill level based on each user.In some embodiments, one or more exercise model is by the data genaration of the one or more suitable lattice body-building professional person from the exercise carrying out defining.In some embodiments, one or more exercise model by from the exercise correctly not carrying out defining to simulate the data genaration of the suitable lattice body-building professional person of common exercise posture problem.In other embodiments, one or more exercise model is by the data genaration of suitable lattice body-building professional person of tempering posture from the exercise correctly carrying out defining with illustrated example.In other embodiments, each exercise model is generated by the average data of the sole user from the exercise carrying out defining with different multiplicity.In further embodiment, each exercise model generates by carrying out the one dimension of user of the exercise defined, two dimension or three-dimensional body motion data.In further embodiment, the body motion data of carrying out the user of the exercise defined is from the acceleration information of accelerometer or from gyrostatic angular velocity data.In other embodiment, body motion data is received from pressure transducer, GPS, timer or thermometer.In some embodiments, the 3D body kinematics related data of user comprises one dimension, two dimension or three-dimensional distance, displacement, acceleration, angular velocity, linear momentum, speed, coordinate, geo-location, power, moment of torsion, radius, circumference, highly.In some embodiments, received data are also relevant with exercise environment, and described exercise environment comprises atmospheric pressure, hydraulic pressure, wind speed, water speed, gravity horizontal or temperature.In some embodiments, one or more exercise model is the input to the probability analysis in individual exercise analysis application.

individual activity analytical applications

In some embodiments, equipment described herein, platform and medium comprise individual activity analytical applications or its use.In some embodiments, individual activity analytical applications comprises the software module for receiving the data be associated with the body kinematics of user under three dimensions.In further embodiment, the data be associated with the body kinematics of user under three dimensions comprise acceleration information and/or angular velocity data.In other embodiment, it is one or more that the data receiver be associated with the body kinematics of user under three dimensions is selected in accelerometer or gyroscope.In other embodiments, the data be associated with the body kinematics of user under three dimensions are acceleration informations.In further embodiment, the data receiver be associated with the body kinematics of user under three dimensions is from one or more accelerometer.In some embodiments, acceleration information comprises acceleration information (for any single dimension, having forward and negative sense) under a Spatial Dimension, two Spatial Dimensions or three Spatial Dimensions and/or a time dimension or its combination.In some embodiments, angular velocity data comprises orientation information (for any single dimension, having forward and negative sense) under a Spatial Dimension, two Spatial Dimensions or three Spatial Dimensions and/or a time dimension or its combination.In some embodiments, acceleration information and angular velocity data are 3 × 3 vectors.In other embodiments, acceleration information and angular velocity data are four dimensional vectors.In other embodiment, the data receiver be associated with the body kinematics of user under three dimensions is from pressure transducer, GPS, timer, speed pickup, vibration transducer or thermometer.In some embodiments, the data be associated with the body kinematics of user under three dimensions comprise one dimension, two dimension or three-dimensional distance, frequency, phase place, displacement, acceleration, angular velocity, linear momentum, speed, coordinate, geo-location, power, moment of torsion, radius, circumference, highly, the duration, pressure etc.In further embodiment, the data be associated with the body kinematics of user under three dimensions comprise to one dimension, two dimension or three-dimensional distance, displacement, acceleration, angular velocity, linear momentum, speed, coordinate, geo-location, power, moment of torsion, radius, circumference, highly, the duration, the mathematics manipulation of pressure etc. or statistical treatment.In some embodiments, also relevant with exercise environment with the data that the body kinematics of user under three dimensions is associated, described exercise environment comprises atmospheric pressure, water resistance, windage resistance, hydraulic pressure, wind speed, water speed, gravity horizontal or temperature.

In some embodiments, individual activity analytical applications comprises the software module being arranged to and personal computing devices being placed in mode of learning.In some embodiments, mode of learning comprises the data recording and be associated with the body kinematics of user under a dimension, two dimensions or three dimensions carrying out the activity defined.In further embodiment, the data be associated with the body kinematics of user under three dimensions are acceleration information and/or the angular velocity data of the user carrying out the activity defined, to generate the statistical activity model for this activity.In some embodiments, user is one or more in the body-building professional person of suitable lattice, coach, private religion, expert, sportsman, professional athlete, teacher, director, lecturer, robot etc.In some embodiments, activity relates to the sports of the body kinematics under a dimension, two dimensions or three dimensions.In further embodiment, activity comprise brush teeth, shower, water, toilet draws water (plumbing), pruning, gunshot, driving, by bike, paratrooper's shooting, cuttage, drawing, the health that produces because of artillery recoil power move, typewrite, sew, draw, write, instrument playing, cleaning, gardening, swim, shake hands, rectification, uncork, operate video games, dancing etc.In further embodiment, the statistical activity model of the activity of definition generates separately based on Activity Type, age, body weight, height, sex, arm exhibition, multiplicity or this type of information.

In some embodiments, each motility model is generated by the average data of the one or more users from the activity carrying out defining.In further embodiment, average data is the weighted mean data of the professional skill level based on each user.In some embodiments, one or more motility model is by the data genaration of the one or more suitable lattice body-building professional person from the activity carrying out defining.In some embodiments, one or more motility model by from the activity correctly not carrying out defining to simulate the data genaration of the suitable lattice body-building professional person of common activity posture problem.In other embodiments, one or more motility model by from the activity correctly carrying out defining with the data genaration of the suitable lattice body-building professional person of illustrated example sexuality posture.In other embodiments, each motility model is generated by the average data of the sole user from the activity carrying out defining with multiple multiplicity.In further embodiment, statistical model is generated by the 3D body kinematics of the user carrying out the activity defined.

In some embodiments, individual activity analytical applications also comprises the software module being arranged to and described equipment being placed in normal mode, normal mode comprise to three dimensional body move the market demand probability analysis that is associated identifying Activity Type, by the comparing of motility model with record, Activity Type classified and identify the multiplicity of this activity.In some embodiments, three dimensional body motion is the original motion related data of collecting from personal computing devices.In other embodiments, before applied probability analysis, based on the raw data of collecting from motion sensor, pre-service is carried out to 3D body kinematics related data.In further embodiment, it is one or more that pre-service comprises in the following: space, being averaging of time or frequency dependence, quantize, denoising, smoothing, linear or nonlinear fitting, filtering, weighting, cut position, deletion, change, take advantage of, subtract, remove, interpolation, differentiate, round up, recombinate, extract square root, exponentiation etc.In other embodiment, pre-service comprises mathematical operation to raw data or statistical calculation, comprise calculate scale, z-scoring, quantize, PCA analyzes (principal component analysis (PCA)), deducts the average of raw data, the standard deviation etc. divided by raw data.

In some embodiments, be used for comprising the probability analysis that activity is classified utilizing neural network, context tree weighting, hidden Markov model, dynamic system, principal component analysis (PCA), k-mean cluster, dynamic bayesian network, mixture model, regression model, Markov random field, condition random field, template matches, dynamic probability graphical model, K-arest neighbors model, patent model of cognition, Statistical learning model, machine learning model or its combination.In some embodiments, the input of probability analysis comprises the undressed body motion data of user under a dimension, two dimensions or three dimensions of the activity carrying out one or more definition.In further embodiment, the user that the input of probability analysis comprises the activity carrying out one or more definition under a dimension, two dimensions or three dimensions through pretreated body motion data.In further embodiment, pre-service is undertaken by mathematical operation or statistical calculation.In some embodiments, the input of probability analysis comprises the motility model of one or more record.In some embodiments, the output of probability analysis comprises the vector etc. of probability, the vector of probability, conspicuousness, the vector of conspicuousness, p value, the vector of p value, evaluated error, evaluated error.In further embodiment, output valve is more than or equal to 0 and is less than or equal to 1.In further embodiment, the output of probability analysis have fixing and.In other embodiment, the output of probability analysis and be 1.

In some embodiments, individual activity analytical applications also comprises and being arranged to the market demand relative method of 3D body kinematics with the software module of marking to the activity posture of user.In further embodiment, scoring comprises average score, the highest scoring of individual, individual minimum scoring, the scoring distribution in a period of time, the distribution of the scoring in multiplicity or this type of combination.Relative method comprise the difference of two squares and, statistical discrepancy, root-mean-square-deviation, root-mean-square-deviation and, root mean square and, return, Mahalanobis generalised distance or this type of combination.In further embodiment, use is selected from the activity posture of the letter scale in the list of A, B, C, D, E and F to user and marks.In other embodiments, the activity posture of the centile of usable range between 100 hundredths to 0 hundredths to user is marked.In other embodiments, the activity posture of the numerical grade of usable range between 10 to 0,5 to 0 or 4 to 0 to user is marked.In some embodiments, scoring comes from raising within a period of time or multiplicity of the body steadiness of user, the sports coordination of user, user or its combination at least in part.In some embodiments, scoring comes from comparing of the data of the 3D body kinematics of user and the motility model generated by different user or the motility model that generated by the mean value of the data of at least two other users at least in part.In further embodiment, different user or other users are the body-building professional person of one or more suitable lattice, coach, private religion, expert, sportsman, professional athlete, robot etc.

In some embodiments, described application also comprises the software module being arranged to and presenting user interface, and user interface allows mutual via the user-equipment of input equipment.In further embodiment, input equipment comprises touch-screen, button, button, rolling, mouse, keyboard, sensing equipment, telepilot, microphone, motion sensor, eye movement sensor, temperature sensor, optical sensor or pressure transducer.In further embodiment, comprise touch alternately, click, vibrate, shake, touch, highlighted, draw circle, sketch outline, gesture, sensing, slip, pressing, eye movement or intersection.In some embodiments, user interface allows to show message on equipment, selects or prompting that amendment equipment mode, rest timer, the immediate feedback via sound, light or vibration, equipment Alignment, error reporting, error correcting, movable relevant prompting, physiological data are relevant or its combination.In further embodiment, immediate feedback comprises via sound, light or the feedback of vibration to the performance that the physiological data of user or the activity of user are correlated with.In some embodiments, on equipment, display comprises the number, exercise journal, user profiles etc. of display scoring, Activity Type, multiplicity, muscular fatigue degree, active duration, message specific to activity, user's physiological data, device-dependent message, storage space use, battery electric quantity, stored correlated activation.In further embodiment, graphic user interface allows user to utilize one or more mathematical operation or statistical calculation to make correction to activity related information and/or activity related information.In further embodiment, activity related information comprises the derivative information of Activity Type, multiplicity, activity log, scoring, average score, average duration, average heavy burden, total duration, overall score, minimum or the highest scoring, scoring daily record, heavy burden, duration or any activity.In further embodiment, use the correction of activity related information to upgrade statistical study or probability analysis method.

In some embodiments, activity is weight training activity, and comprises specific to the message of activity: the time of cost, multiplicity, weight are too heavy, weight is too light, weight change too many, motion is too fast, health too not steadily, posture is too incorrect, posture is too inharmonious, the movable number that stores and the rectification opinion about activity posture.In some embodiments, the message specific to equipment comprises: bluetooth connects, bluetooth disconnects, the total activity number stored, newly-increased Activity Type, the Activity Type of deletion, Activity Type mistake, storage area are low, battery electric quantity notice, the geo-location detected, reset timer start, the stopping of reset timer, geo-location mistake, the environment detected, environment error or this type of combination.

In some embodiments, individual activity analytical applications comprise be arranged to or from activity analysis server application transport or receive the software module of data be associated with the 3D body kinematics of the user carrying out the activity defined.In further embodiment, transmission or reception are direct.In other embodiments, transmission or reception are indirectly, and wherein first data are transferred to digital device.In further embodiment, digital device is computing machine, mobile device, online account, online database, digital storage media, server, hub, hard disk drive, usb driver, cloud storage space etc.

In some embodiments, individual activity analytical applications also comprises the software module being arranged to and presenting and allow user to create the interface of personal profiles.In further embodiment, profile comprise body weight, height, the age, sex, arm exhibition, body-building professional skill, moving target, scoring target, to wearing the preference of described equipment, activity log, scoring record, statistical study etc. to activity related information.

In some embodiments, the server application market demand probability analysis that comprises the 3D body kinematics of the user be arranged to the activity defined with identify life event, by with one or more comparison in statistical activity model and Activity Type being classified and the software module of the multiplicity of mark activity.In further embodiment, the data of 3D body kinematics comprise acceleration information and angular velocity data.

In some embodiments, described application comprises and being arranged to acceleration information and the analysis of angular velocity data applied statistics with the software module of marking to the activity posture of described user.In further embodiment, scoring comprises average score, the highest scoring of individual, individual minimum scoring, the scoring distribution in a period of time, the distribution of the scoring in multiplicity or this type of combination.Relative method comprise the difference of two squares and, root-mean-square-deviation, root-mean-square-deviation and, root mean square and, return, Mahalanobis generalised distance or this type of combination.In further embodiment, use is selected from the activity posture of the letter scale in the list of A, B, C, D, E and F to user and marks.In other embodiments, the activity posture of the centile of usable range between 100 hundredths to 0 hundredths to user is marked.In other embodiments, the activity posture of the numerical grade of usable range between 10 to 0,5 to 0 or 4 to 0 to user is marked.In some embodiments, scoring comes from raising within a period of time or multiplicity of the body steadiness of user, the sports coordination of user, user or its combination at least in part.In some embodiments, scoring comes from comparing of the data of the 3D body kinematics of user and the motility model generated by different user or the motility model that generated by the mean value of the data of at least two other users at least in part.In further embodiment, different user or other users are the body-building professional person of one or more suitable lattice, coach, private religion, expert, sportsman, professional athlete, robot etc.

In some embodiments, individual activity analytical applications also comprises the software module being arranged to and described equipment being placed in calibration mode, calibration mode comprises and to move the market demand probability analysis be associated to one or more three dimensional body of specific user, relies on parameter with the user identified in probability analysis.In some embodiments, three dimensional body motion is the original motion related data of collecting from personal computing devices.In other embodiments, before applied probability analysis, based on the raw data of collecting from motion sensor, pre-service is carried out to 3D body kinematics related data.In further embodiment, it is one or more that pre-service comprises in the following: space, being averaging of time or frequency dependence, quantize, denoising, smoothing, linear or nonlinear fitting, filtering, weighting, cut position, deletion, change, take advantage of, subtract, remove, interpolation, differentiate, round up, recombinate, extract square root, exponentiation etc.In other embodiment, pre-service comprises mathematical operation to raw data or statistical calculation, comprise calculate scale, z-scoring, quantize, PCA analyzes (principal component analysis (PCA)), deducts the average of raw data, the standard deviation etc. divided by raw data.

activity analysis server is applied

In some embodiments, equipment described herein, platform and medium comprise the application of activity analysis server or its use.In some embodiments, server application comprises the database of statistical activity model.In further embodiment, database comprises at least 1, at least 2, at least 5, at least 8, at least 10, at least 20, at least 40, at least 50, at least 80, at least 100, at least 150, at least 250, at least 200, at least 300, at least 400 or at least 500 motility models, and wherein each model is associated with specific activity.In further embodiment, specific motility model and Activity Type, user's sex, age of user, user's weight, user's height, user's arm are opened up, multiplicity, active duration or this type of combination store in a database explicitly.In some embodiments, each motility model is generated by the average data of the multiple users from the activity carrying out defining.In further embodiment, average data is the weighted mean data of the professional skill level based on each user.In some embodiments, one or more motility model is by the data genaration of the one or more suitable lattice body-building professional person from the activity carrying out defining.In some embodiments, one or more motility model by from the activity correctly not carrying out defining to simulate the data genaration of the suitable lattice body-building professional person of common activity posture problem.In other embodiments, one or more motility model by from the activity correctly carrying out defining with the data genaration of the suitable lattice body-building professional person of illustrated example sexuality posture.In other embodiments, each motility model is generated by the average data of the sole user from the activity carrying out defining with different multiplicity.In further embodiment, each motility model generates by carrying out the one dimension of user of the activity defined, two dimension or three-dimensional body motion data.In further embodiment, the body motion data of carrying out the user of the activity defined be received from accelerometer acceleration information or be received from gyrostatic angular velocity data.In other embodiment, body motion data is received from pressure transducer, GPS, timer or thermometer.In some embodiments, the 3D body kinematics related data of user comprises one dimension, two dimension or three-dimensional distance, displacement, acceleration, angular velocity, linear momentum, speed, coordinate, geo-location, power, moment of torsion, radius, circumference, highly.In some embodiments, received data are also relevant with exercise environment, and described exercise environment comprises atmospheric pressure, hydraulic pressure, wind speed, water speed, gravity horizontal or temperature.

In some embodiments, the application of activity analysis server comprises the software module being arranged to and carrying out the 3D body kinematics related data of the user of the activity defined from personal computing devices reception.In further embodiment, server application receives the 3D body kinematics related data of carrying out the user of the activity defined from least 5, at least 8, at least 10, at least 20, at least 30, at least 40, at least 50, at least 80, at least 100, at least 200, at least 500, at least 1000, at least 5000, at least 10000 or at least 20000 personal computing devices.

In some embodiments, the server application market demand probability analysis that comprises the 3D body kinematics of the user be arranged to the activity defined with identify life event, by with one or more comparison in statistical activity model and Activity Type is classified and/or identifies the software module of multiplicity of activity.In some embodiments, server is applied to comprise and is arranged to the analysis of 3D body motion data applied statistics with the software module of marking to the activity posture of user.In further embodiment, the data of 3D body kinematics comprise acceleration information and angular velocity data.In further embodiment, the data of 3D body kinematics comprise one dimension, two dimension or three-dimensional distance, displacement, acceleration, angular velocity, linear momentum, speed, coordinate, geo-location, power, moment of torsion, radius, circumference, highly.In further embodiment, the 3D body kinematics related data of user comprise to one dimension, two dimension or three-dimensional distance, displacement, acceleration, angular velocity, linear momentum, speed, coordinate, geo-location, power, moment of torsion, radius, circumference, highly, the duration, the mathematics manipulation of pressure etc. or statistical treatment.In some embodiments, received data are also relevant with exercise environment, and described exercise environment comprises atmospheric pressure, hydraulic pressure, wind speed, water speed, gravity horizontal or temperature.

In some embodiments, the application of activity analysis server also comprises the software module being arranged to and presenting the interface allowing user's establishment, amendment, deletion or preserve personal profiles.In further embodiment, profile comprise body weight, height, the age, sex, arm exhibition, body-building professional skill, to the preference etc. wearing described equipment.

activity Type

In some embodiments, each motility model is associated with specific sports.In further embodiment, specific motility model and Activity Type, user's sex, age of user, user's weight, user's height, user's arm are opened up, multiplicity, active duration or this type of combination store in a database explicitly.In some embodiments, activity analysis server application or individual activity analytical applications database in add, amendment or delete motility model.In some embodiments, each motility model is generated by the average data of the multiple users from the activity carrying out defining.In further embodiment, average data is the weighted mean data of the professional skill level based on each user.In some embodiments, one or more motility model is by the data genaration of the one or more suitable lattice body-building professional person from the activity carrying out defining.In some embodiments, one or more motility model by from the activity correctly not carrying out defining to simulate the data genaration of the suitable lattice body-building professional person of common activity posture problem.In other embodiments, one or more motility model by from the activity correctly carrying out defining with the data genaration of the suitable lattice body-building professional person of illustrated example sexuality posture.In other embodiments, each motility model is generated by the average data of the sole user from the activity carrying out defining with different multiplicity.In further embodiment, each motility model generates by carrying out the one dimension of user of the activity defined, two dimension or three-dimensional body motion data.In further embodiment, the body motion data of carrying out the user of the activity defined is from the acceleration information of accelerometer or from gyrostatic angular velocity data.In other embodiment, body motion data is received from pressure transducer, GPS, timer or thermometer.In some embodiments, the 3D body kinematics related data of user comprises one dimension, two dimension or three-dimensional distance, displacement, acceleration, angular velocity, linear momentum, speed, coordinate, geo-location, power, moment of torsion, radius, circumference, highly.In some embodiments, received data are also relevant with exercise environment, and described exercise environment comprises atmospheric pressure, hydraulic pressure, wind speed, water speed, gravity horizontal or temperature.In some embodiments, one or more motility model is the input to the probability analysis in individual activity analytical applications.

digital processing device

In some embodiments, platform described herein, medium, methods and applications comprise digital processing device, processor or its use.In further embodiment, digital processing device comprises one or more hardware CPU (central processing unit) (CPU) of the function of implementation equipment.In other embodiment, digital processing device also comprises the operating system being arranged to and performing executable instruction.In some embodiments, digital processing device is connected to computer network alternatively.In further embodiment, digital processing device is connected to the Internet alternatively, to make its access WWW.In other embodiment, digital processing device is connected to cloud computing foundation structure alternatively.In other embodiments, digital processing device is connected to Intranet alternatively.In other embodiments, digital processing device is connected to data storage device alternatively.

According to description herein, lift non-limiting example, suitable digital processing device comprises server computer, desk-top computer, laptop computer, notebook, Subnotebook, net book computing machine, online flat computer, machine top computing machine, handheld computer, Internet appliance, intelligent movable phone, flat computer, personal digital assistant, electronic game console and carrier.Those skilled in the art will recognize that many smart phones are suitable for using in system described herein.Those of skill in the art also will appreciate that selected TV, video player and the digital music player having optional computer network and connect is suitable for using in system described herein.Suitable flat computer comprises those flat computers known to those skilled in the art, that have pamphlet, flat board and convertible configuration.

In some embodiments, digital processing device comprises the operating system being arranged to and performing executable instruction.Operating system is such as the software comprising program and data, the hardware of this software administration equipment and be provided for the service performing application.Lift non-limiting example, those skilled in the art will recognize that suitable server OS comprise FreeBSD, OpenBSD, linux, macOSX windows and lift non-limiting example, those skilled in the art will recognize that suitable PC operating system comprises macOS and the operating system of similar UNIX, such as in some embodiments, operating system is provided by cloud computing.Those of skill in the art also will appreciate that suitable intelligent movable telephone operating system comprises, lift non-limiting example, oS, researchIn blackBerry windows oS, windows oS, and

In some embodiments, described equipment comprises storage and/or memory device.To store and/or memory device is one or more physical units for temporarily or for good and all storage data or program.In some embodiments, described equipment is volatile memory and needs electric power to maintain stored information.In some embodiments, described equipment be nonvolatile memory and when described digital processing device is not energized keep stored by information.In further embodiment, nonvolatile memory comprises flash memory.In some embodiments, nonvolatile memory comprises dynamic RAM (DRAM).In some embodiments, nonvolatile memory comprises ferroelectric RAM (FRAM).In some embodiments, nonvolatile memory comprises phase change random access memory devices (PRAM).In some embodiments, nonvolatile memory comprises magnetoresistive RAM (MRAM).In other embodiments, described equipment is storage facilities, lifts nonrestrictive example, and this storage facilities comprises CD-ROM, DVD, flash memory, disc driver, tape drive, CD drive and the reservoir based on cloud computing.In further embodiment, storage and/or memory device are the combinations of the equipment such as all those equipment as disclosed herein.

In some embodiments, digital processing device comprises the display for sending visual information to user.In some embodiments, display is cathode-ray tube (CRT) (CRT).In some embodiments, display is liquid crystal display (LCD).In further embodiment, display is Thin Film Transistor-LCD (TFT-LCD).In some embodiments, display is Organic Light Emitting Diode (OLED) display.In each further embodiment, OLED display is passive matrix type OLED (PMOLED) or active matric OLED (AMOLED) display.In some embodiments, display is plasma display.In some embodiments, display is Electronic Paper or electric ink.In other embodiments, display is video projector.In other embodiment, display is the combination of the equipment such as all those equipment as disclosed herein.

In some embodiments, digital processing device comprises the input equipment for receiving from the information of user.In some embodiments, input equipment is keyboard.In some embodiments, input equipment is sensing equipment, and lift non-limiting example, it comprises mouse, trackball, tracking plate, operating rod, game console or pointer.In some embodiments, input equipment is touch-screen or multi-point touch panel.In other embodiments, input equipment is used to the microphone catching voice or other Speech inputs.In other embodiments, input equipment is used to video camera or other sensors of capturing motion or vision input.In further embodiment, input equipment is Ken Naite (Kinect), strict dynamic (LeapMotion) etc.In other embodiment, input equipment is the combination of the equipment such as all those equipment as disclosed herein.

non-transient computer-readable recording medium

In some embodiments, platform described herein, medium, methods and applications comprise one or more non-transient computer-readable recording mediums of the program of being encoded with, and described program comprises the instruction that can be performed by the operating system of the digital processing device of networking alternatively.In further embodiment, computer-readable recording medium is the tangible components of digital processing device.In some embodiments again, computer-readable recording medium can remove from digital processing device alternatively.In some embodiments, lift non-limiting example, computer-readable recording medium comprises CD-ROM, DVD, flash memory, solid-state memory, disc driver, tape drive, CD drive, cloud computing system and service etc.In some cases, program and instruction for good and all, substantially for good and all, semi-permanently or non-transient be coded on medium.

computer program

In some embodiments, platform described herein, medium, methods and applications comprise at least one computer program or its use.Computer program comprises and can perform in the CPU of digital processing device, write to perform the instruction sequence of appointed task.Computer-readable instruction can be implemented as program module, such as function, object, application programming interface (API), data structure etc., and it performs specific task or realizes specific abstract data type.According to disclosure provided in this article, those skilled in the art will recognize that computer program can be write with the various versions of various language.

In various environment, can combine the function of computer-readable instruction as required or distribute.In some embodiments, computer program comprises an instruction sequence.In some embodiments, computer program comprises multiple instruction sequence.In some embodiments, computer program provides from a position.In other embodiments, computer program provides from multiple position.In various embodiments, computer program comprises one or more software module.In various embodiments, computer program comprises one or more network application, one or more Mobile solution, one or more independent utility, one or more network browser card, extension, add-in, additive term or its combination partial or completely.

network application

In some embodiments, computer program comprises network application.According to disclosure provided in this article, those skilled in the art will recognize that, in various embodiments, network application utilizes one or more software architecture and one or more Database Systems.In some embodiments, network application is created in such as .NET or on the software architecture such as RubyonRails (RoR).In some embodiments, network application utilizes one or more Database Systems, lift non-limiting example, it comprises system R, non-relational database system, OODBS, linked database system and XML database system.In further embodiment, lift non-limiting example, suitable system R comprises sQLServer, mySQL tMand those of skill in the art also will appreciate that, in various embodiments, network application is write with one or more versions of one or more language.Network application can with one or more markup languages, represent that definitional language, client-side scripting language, server end code speech, data base query language or its combination are write.In some embodiments, network application is write with markup languages such as such as HTML (Hypertext Markup Language) (HTML), extensible HyperText Markup Language (XHTML) or extend markup languages (XML) to a certain extent.In some embodiments, with such as Cascading Style Sheet (CSS) etc., network application represents that definitional language is write to a certain extent.In some embodiments, network application to a certain extent with such as asynchronous Javascript and XML (AJAX), actionscript, Javascript or write Deng client-side scripting language.In some embodiments, network application to a certain extent with such as Active Server Pages (ASP), perl, Java tM, JavaServerPages (JSP), HyperText Preprocessor (PHP), Python tM, Ruby, Tcl, Smalltalk, or the server end code speech such as Groovy is write.In some embodiments, network application is write with data base query languages such as such as Structured Query Language (SQL) (SQL) to a certain extent.In some embodiments, network application is integrated with enterprise servers product, such as in some embodiments, network application comprises media player element.In various further embodiment, media player element utilize in many suitable multimedia technologies one or more, lift non-limiting example, it comprises hTML5, java tMand

mobile solution

In some embodiments, computer program comprises the Mobile solution being provided to mobile digital treatment facility.In some embodiments, when manufacture mobile digital treatment facility, Mobile solution is supplied to this mobile digital treatment facility.In other embodiments, Mobile solution is provided to mobile digital treatment facility via computer network described herein.

According to disclosure provided in this article, Mobile solution uses hardware known in the art, language and development environment, created by technology well known by persons skilled in the art.Those skilled in the art will recognize that Mobile solution is write with multilingual.Lift non-limiting example, suitable programming language comprises C, C++, C#, Objective-C, Java tM, Javascript, Pascal, ObjectPascal, Python tM, Ruby, VB.NET, WML and there is or do not have the XHTML/HTML of CSS or its combination.

Suitable Mobile solution development environment can obtain from some sources.Lift non-limiting example, commercially available development environment comprise AirplaySDK, alcheMo, celsius, Bedrock, FlashLite .NETCompactFramework, Rhomobile and WorkLight mobile platform.Other development environments are free, and lift non-limiting example, it comprises Lazarus, MobiFlex, MoSync and Phonegap.In addition, mobile device manufacturers releasing software development kit, lift non-limiting example, described SDK (Software Development Kit) comprises iPhone and iPad (IOS) SDK, Android tMsDK, sDK, BREWSDK, oSSDK, SymbianSDK, webOSSDK and mobileSDK.

Those skilled in the art will recognize that, some business forums can be used for the issue of Mobile solution, and lift non-limiting example, described business forum comprises application shop, Android tMmarket, the application world, the application shop for Palm equipment, the application catalogue for webOS, for movement market, for the Ovi shop of equipment, apps and dSi shop.

independent utility

In some embodiments, computer program comprises independent utility, and described independent utility is as independently computer procedures and the program run, but not the additive term of existing process, such as, not plug-in unit.Person of skill in the art will appreciate that, often compile independent utility.Compiler is (one or more) computer program source code write with programming language being converted to the such as binary object code such as assembly language or machine code.Lift non-limiting example, suitable compiling programming language comprises C, C++, Objective-C, COBOL, Delphi, Eiffel, Java tM, Lisp, Python tM, VisualBasic and VB.NET or its combination.Often perform compiling at least in part to create executable program.In some embodiments, computer program comprises one or more executable application through compiling.

software module

In some embodiments, platform described herein, medium, methods and applications comprise software, server and/or database module or its use.According to disclosure provided in this article, software module uses machine known in the art, software and language to be created by technology well known by persons skilled in the art.Software module disclosed herein realizes in many ways.In various embodiments, software module comprises file, code segment, programming object, programming structure or its combination.In various further embodiment, software module comprises multiple file, multiple code segment, multiple programming object, multiple programming structure or its combination.In various embodiments, lift non-limiting example, one or more software module package includes network application, Mobile solution and independent utility.In some embodiments, software module is arranged in a computer program or application.In other embodiments, software module is arranged in a more than computer program or application.In some embodiments, software module trustship is on a machine.In other embodiments, software module trustship is on a more than machine.In further embodiment, software module trustship is on cloud computing platform.In some embodiments, on software module trustship one or more machine in one location.In other embodiments, on software module trustship one or more machine in a more than position.

database

In some embodiments, platform described herein, system, medium and method comprise one or more database or its use.According to disclosure provided in this article, those skilled in the art will recognize that many databases are suitable for storage and retrieval bar code, route, parcel, user or the network information.In various embodiments, lift non-limiting example, suitable database comprises relevant database, non-relational database, object-oriented database, object database, entity relationship model database, linked database and XML data storehouse.In some embodiments, database is based on the Internet.In further embodiment, database is network.In other embodiment, database is based on cloud computing.In other embodiments, database is based on one or more local computer storage facilities.Although illustrate and describe the preferred embodiment of the present invention herein, it will be apparent to one skilled in the art that what such embodiment just provided in an illustrative manner.Those skilled in the art now will expect many changes, change without deviating from the invention and substitute.Should be appreciated that and putting into practice in process of the present invention the various replacement schemes that can adopt embodiment of the present invention described herein.

network browser card

In some embodiments, computer program comprises network browser card.In the calculation, plug-in unit is the one or more component softwares adding concrete function to larger software application.The fabricator of software application supports plug-in unit, can create to make third party developer and make the ability of application extension, can support to add new feature easily and can reduce apply size.Plug-in unit can realize when being subject to supporting customizing the function of software application.Such as, plug-in unit is generally used in web browser, playing video, produces interactive, Scan for Viruses and shows specific file type.Those skilled in the art will be familiar with some network browser cards, comprise player, with in some embodiments, toolbar comprises one or more web browser extension, add-in or additive term.In certain embodiments, tool bar comprises one or more browser hurdle, toolbar or desktop toolbar.

According to disclosure provided in this article, those skilled in the art will recognize that some plug-in unit frameworks are available, it makes it possible to various programming language to develop plug-in unit, and lift non-limiting example, described programming language comprises C++, Delphi, Java tM, PHP, Python tMand VB.NET or its combination.

Web browser (also referred to as explorer) is the software application being designed to use together with the digital processing device of networking, for retrieving, presenting and travel through the information resources in WWW.Lift non-limiting example, suitable web browser comprises and KDEKonqueror.In some embodiments, web browser is mobile network's browser.Mobile network's browser (also referred to as microbrowser, mini browser and wireless browser) is designed to use on mobile digital treatment facility, lift non-limiting example, described mobile digital treatment facility comprises handheld computer, flat computer, net book computing machine, quasi-notebook PC, smart phone, music player, personal digital assistant (PDA) and hand-held electronic games system.Lift non-limiting example, suitable mobile network's browser comprises browser, RIM browser, blazer, browser, for movement mobile, basicWeb, browser, mobile and pSP tMbrowser.

Embodiment

Following illustrative embodiment is the representative of embodiment of application described herein, system, method and medium, and does not mean that by any way and become restrictive.

embodiment 1 – learns a kind of exercise newly

Weight lifting coach is at his right hand weared on wrist personal computing devices.His his body weight of typing, height, age and sex, as the information stored together with the exercise carried out with its selection.He goes back weight and the number of the dumbbell of its choice for use of typing.After his correctly typing is newly tempered markers and started record, he makes with the hands (every hand holds the dumbbell of 10 pounds) carries out flat chest dumbbell and praises.He repeats 3 groups of same exercises, often organizes repetition 10 times.In order to make muscular fatigue minimize, often group completed in 1 minute, and was separated by the interval of 2 minutes between each group.After he completes a whole set of exercise, he uses the user interface on personal computing devices to preserve this new exercise.Confidence level is greater than default threshold, and exercise data and exercise types, body weight, height, age, sex and dumbbell number and weight are saved explicitly and are added in the database of exercise.

embodiment 2 – carries out the exercise of recording

Postgraduate he right hand weared on wrist personal computing devices and select him to be stored in user profiles in this personal computing devices via graphic user interface.After selecting and confirm its user profiles, he enters exercise mode.This postgraduate makes with the hands (every hand holds the dumbbell of 3 pounds) carries out flat chest dumbbell and praises.He repeats same exercise totally 1 group, often organizes repetition 10 times.His exercise data and the exercise types recorded are compared, does not calculate and temper scoring and on equipment, show message-" weight is too light ".He is switched to the dumbbell of 10 pounds and uses its right arm to repeat flat chest dumbbell to praise.He repeats another 10 times to this exercise and points out this equipment again to calculate scoring.Demonstrating the message of " health is too unstable ", is 50% along with the scoring of exercise posture.This postgraduate determines again to attempt and choice for use both hands and 10 pounds of dumbbells repeat flat chest dumbbell praises.He repeats this exercise 10 times in earnest, therefore slow in one's movements, employs 2.5 minutes.Display is tempered posture scoring and be depicted as 70%, along with message " action is too slow or weight is too heavy ".Carry out for the third time in the trial of this exercise at him, he uses graphic user interface to open instant vibrational feedback.When he carries out first three repetition of this exercise, provide a vibration as the instruction maintaining good posture, repeat once this is because he reaches 15 seconds; Provide two continuous print vibrations, as the instruction of the incorrect posture caused due to muscular fatigue.Repeat based on whole 20 times, total posture scoring that he attempts for the third time is 85%.

Claims (30)

1. a personal computing devices, comprising:
A. processor, plate carry storer, accelerometer, gyroscope and display;
B. comprise the computer program that can be performed to create by digital processing device the instruction that exercise analysis is applied, described exercise analysis application comprises:
I. be arranged to and receive acceleration information and from the software module of described gyroscope acceptance angle speed data, described acceleration information and described angular velocity data are associated with the body kinematics of user under three dimensions from described accelerometer;
Ii. be arranged to the software module described equipment being placed in mode of learning, described mode of learning comprises record and carries out the acceleration information of the described user of the exercise defined and angular velocity data to generate the statistics exercise model for described exercise;
Iii. be arranged to the software module described equipment being placed in normal mode, described normal mode comprises described acceleration information and the analysis of described angular velocity data applied probability to identify exercise event, classified by the comparing of exercise model with record and identified the multiplicity of described exercise described exercise; And
Iv. be arranged to described acceleration information and the analysis of described angular velocity data applied statistics with the software module of marking to the exercise posture of described user.
2. equipment according to claim 1, it is wearable that wherein said equipment is suitable for user.
3. equipment according to claim 2, wherein said equipment is suitable for can be worn by described user's wrist.
4. equipment according to claim 2, wherein said equipment comprises wearable adapter, and described wearable adapter reversibly can connect from described equipment, to form modular design.
5. equipment according to claim 1, also comprises biology sensor, and described biology sensor is for measuring the physiological parameter of described user.
6. equipment according to claim 5, wherein said biology sensor is selected from and comprises every group below: heart rate monitor, thermometer, respirometer, glucose monitoring devices, electrolyte sensor and diagometer.
7. equipment according to claim 5, wherein said biology sensor is optical biosensor.
8. equipment according to claim 5, wherein said physiological parameter is selected from and comprises every group below: heart rate, skin temperature, respiratory rate, electrodermal response and aquation.
9. equipment according to claim 5, wherein said application also comprises the software module being arranged to and presenting graphic user interface, and described graphic user interface comprises the rest timer based on heart rate.
10. equipment according to claim 1, also comprises Geographical Location element.
11. equipment according to claim 1, also comprise wireless communication unit.
12. equipment according to claim 11, wherein said wireless communication unit is bluetooth module or ANT+ module.
13. equipment according to claim 1, are wherein used for comprising the probability analysis that described exercise is classified utilizing neural network, context tree weighting, hidden Markov model or its combination.
14. equipment according to claim 1, the sports coordination of the body steadiness coming from described user at least in part of wherein marking, described user or its combination.
15. equipment according to claim 1, comparing of the exercise model that comes from described acceleration information and described angular velocity data and the data genaration by other users at least in part of wherein marking.
16. equipment according to claim 1, wherein mark and come from comparing of described acceleration information and described angular velocity data and the exercise model generated by one or more suitable lattice body-building professional person at least in part.
17. equipment according to claim 1, wherein said exercise is one-sided weight training or bilateral weight training.
18. equipment according to claim 1, wherein said application also comprises the software module being arranged to and presenting user interface on the display, and described user interface comprises described scoring, described exercise, described multiplicity, combines specific to the message of taking exercise or its.
19. equipment according to claim 18, wherein said exercise is weight training, and the described message specific to taking exercise be selected from comprise below suggestion in every group: weight is too heavy, weight is too light, weight change too many, motion is too fast, health too not steadily, fault, posture be too inharmonious and about the rectification opinion of posture.
20. 1 kinds of exercise analysis platforms, comprising:
A. personal computing devices, it comprises processor, plate carries storer, accelerometer, gyroscope, display and communication device, and described equipment is arranged to provides individual exercise analysis to apply, and described individual exercise analysis application comprises:
I. be arranged to and receive acceleration information and from the software module of described gyroscope acceptance angle speed data, described acceleration information and described angular velocity data are associated with the body kinematics of user under three dimensions from described accelerometer;
Ii. the software module to acceleration information described in exercise analysis server application transport and angular velocity data is arranged to;
B. processor-server, it is arranged to provides exercise analysis server to apply, and described exercise analysis server application comprises:
I. add up the database of exercise model, described exercise model is generated by the acceleration information of user and angular velocity data carrying out the exercise defined;
Ii. the software module receiving acceleration information and angular velocity data from described personal computing devices is arranged to;
Iii. be arranged to described acceleration information and the analysis of described angular velocity data applied probability with identify exercise event, by with one or more the comparing and described exercise classified and identifies the software module of the multiplicity of described exercise in described statistics exercise model;
Iv. be arranged to described acceleration information and the analysis of described angular velocity data applied statistics with the software module of marking to the exercise posture of described user.
21. platforms according to claim 20, comprise at least 100, at least 1000 or at least 10,000 personal computing devices.
22. platforms according to claim 20, wherein said individual exercise analysis application also comprises the software module being arranged to and described personal computing devices being placed in mode of learning, and described mode of learning comprises record and carries out the acceleration information of the described user of the exercise defined and angular velocity data to generate the statistics exercise model for described exercise.
23. platforms according to claim 20, the database of wherein said statistics exercise model comprises at least 10, at least 50, at least 100 or at least 500 exercise model, and each exercise model is associated with specific exercise.
24. platforms according to claim 20, wherein each exercise model is generated by the average data of the multiple users from the exercise carrying out defining.
25. platforms according to claim 20, wherein one or more exercise model are by the data genaration of the one or more suitable lattice body-building professional person from the exercise carrying out defining.
26. platforms according to claim 25, wherein one or more exercise model by from the exercise correctly not carrying out defining to simulate the data genaration of the suitable lattice body-building professional person of common exercise posture problem.
27. platforms according to claim 25, wherein one or more exercise model are by the data genaration of suitable lattice body-building professional person of tempering posture from the exercise correctly carrying out defining with illustrated example.
28. platforms according to claim 20, wherein said individual exercise analysis application or the application of described server also comprise the software module being arranged to and presenting and allow described user to create the interface of personal profiles, and described profile comprises body weight, height, sex, arm exhibition and body-building professional skill.
29. 1 kinds are encoded with the non-transient computer-readable recording medium that can be performed the instruction carrying out individual exercise analysis by processor, and described instruction comprises:
A. the software module from comprising accelerometer and gyrostatic personal computing devices reception data is arranged to, described data comprise from the acceleration information of described accelerometer with from described gyrostatic angular velocity data, and described acceleration information and described angular velocity data are associated with the body kinematics of user under three dimensions;
B. be arranged to the software module described equipment being placed in mode of learning, described mode of learning comprises record and carries out the acceleration information of the described user of the exercise defined and angular velocity data to generate the statistics exercise model for described exercise;
C. be arranged to the software module described equipment being placed in normal mode, described normal mode comprises described acceleration information and the analysis of described angular velocity data applied probability to identify exercise event, classified by the comparing of exercise model with record and identified the multiplicity of described exercise described exercise; And
D. be arranged to described acceleration information and the analysis of described angular velocity data applied statistics with the software module of marking to the exercise posture of described user.
30. 1 kinds of non-transient computer-readable recording mediums being encoded with computer program, described computer program comprises and can perform to create by processor the instruction that exercise analysis server applies, and described exercise analysis server application comprises:
A. the database of exercise model is added up, the acceleration information that described exercise model is transmitted by the personal computing devices be associated with the user carrying out the exercise defined and angular velocity data generate, described acceleration information and described angular velocity data comprise the data of X-axis, Y-axis and Z axis separately, and described equipment is in mode of learning;
B. be arranged to the software module receiving acceleration information and the angular velocity data transmitted by the personal computing devices be associated with the user carrying out the exercise defined, described equipment is in normal mode;
C. be arranged to and received acceleration information and angular velocity data applied probability analyzed to identify exercise event, by with one or more comparison in described statistics exercise model and described exercise is classified and identifies the software module of the multiplicity of described exercise;
D. be arranged to received acceleration information and the analysis of angular velocity data applied statistics with the software module of marking to the exercise posture of described user.
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